Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: biotech/medical – Page 1,029

How AI Can Look Into Your Eyes And Diagnose A Devastating Brain Disease

“The eyes are the windows to the soul.” It’s an ancient saying, and it illustrates what we know intuitively to be true — you can understand so much about a person by looking them deep in the eye. But how? And can we use this fact to understand disease?

One company is making big strides in this direction. Israel’s NeuraLight, which just won the Health and Medtech Innovation award at SXSW, was founded to bring science and AI to understanding the brain through the eyes.

A focal disease for NeuraLight is ALS, which is currently diagnosed through a subjective survey of about a dozen questions, followed by tests such as an EEG and MRI.

The patient’s eyes follow dots on a screen, and the AI system measures 106 parameters such as dilation and blink rate in less than 10 minutes. In other words, this will be an AI-enabled digital biomarker.

AI chip race: Google says its Tensor chips compute faster than Nvidia’s A100

It also says that it has a healthy pipeline for chips in the future.

Search engine giant Google has claimed that the supercomputers it uses to develop its artificial intelligence (AI) models are faster and more energy efficient than Nvidia Corporation’s. While processing power for most companies delving into the AI space comes from Nvidia’s chips, Google uses a custom chip called Tensor Processing Unit (TPU).

Google announced its Tensor chips during the peak of the COVID-19 pandemic when businesses from electronics to automotive faced the pinch of chip shortage.

AI-designed chips to further AI development

Interesting Engineering reported in 2021 that Google used AI to design its TPUs. Google claimed that the design process was completed in just six hours using AI compared to the months humans spend designing chips.

For most things associated with AI these days, product iterations occur rapidly, and the TPU is currently in its fourth generation. As Microsoft stitched together chips to power OpenAI’s research requirement, Google also put together 4,000 TPUs to make its supercomputer.

Continue reading “AI chip race: Google says its Tensor chips compute faster than Nvidia’s A100” | >

AGI Unleashed: Game Theory, Byzantine Generals, and the Heuristic Imperatives

Patreon: https://www.patreon.com/daveshap.
GitHub: https://github.com/daveshap.
Cognitive AI Lab Discord: https://discord.gg/yqaBG5rh4j.

Artificial Sentience Reddit: https://www.reddit.com/r/ArtificialSentience/
Heuristic Imperatives Reddit: https://www.reddit.com/r/HeuristicImperatives/

DISCLAIMER: This video is not medical, financial, or legal advice. This is just my personal story and research findings. Always consult a licensed professional.

I work to better myself and the rest of humanity.

Deep-learning aging clock tracks human aging, detects eye and other diseases from retinal images

A team of biomedical researchers has developed a non-invasive, more accurate, and inexpensive “aging clock” for tracking and slowing human aging by examining retinal images and using trained deep-learning models of the eye’s fundus (the deepest area of the eye), using a new “eyeAge” system.

The researchers are affiliated with Buck Institute for Research on Aging, Google Research, Google Health, Zuckerberg San Francisco General Hospital, Post Graduate Institute of Medical Education, and Research (India), and University of California, San Francisco.

Tracking eye changes that accompany aging and age-related diseases: the eyeAge system.

Scientists Find Antibiotic-Free Way to Treat Drug-Resistant Infections

Scientists have found an antibiotic-free way of treating ‘golden staph’ skin infections that are the scourge of some cancer patients, and a threat to hospital-goers everywhere.

The lab study from researchers at the University of Copenhagen utilized an artificial version of an enzyme that’s naturally produced by bacteriophages (viruses that infect bacteria), and used it to eradicate Staphylococcus aureus, or golden staph, in biopsy samples from people with skin lymphoma.

“To people who are severely ill with skin lymphoma, staphylococci can be a huge, sometimes insoluble problem, as many are infected with a type of Staphylococcus aureus that is resistant to antibiotics,” explains immunologist Niels Ødum of the University of Copenhagen.

Biological markers identified as powerful predictors of prostate cancer relapse following radiotherapy

Two key proteins linked to cell division can reliably predict disease recurrence in prostate cancer after radiotherapy treatment, according to new research.

Using an inexpensive and widely available technique in the clinic, the researchers evaluated a range of proteins in tumor biopsies and determined that the phosphatase and tensin homolog (PTEN) and geminin proteins are key markers associated with cancer relapse after radiotherapy.

Based on their results, the team at The Institute of Cancer Research, London, reported that patients with tumors showing loss of PTEN were almost three times more likely to experience recurrence than those with ‘normal’ PTEN. Similarly, the data showed a 70 percent increase in the likelihood of experiencing recurrence in patients with tumors that had a 10 percent increase in geminin.

Genetic analysis tool developed to improve cancer modeling

Lifestyle behaviors such as eating well and exercising can be significant factors in one’s overall health. But the risk of developing cancer is predominantly at the whim of an individual’s genetics.

Our bodies are constantly making copies of our to produce new cells. However, there are occasional mistakes in those copies, a phenomenon geneticists call mutation. In some cases, these mistakes can alter proteins, fuse genes and change how much a gene gets copied, ultimately impacting a person’s risk of developing cancer. Scientists can better understand the impact of mutations by developing predictive models for tumor activity.

Christopher Plaisier, an assistant professor of biomedical engineering in the Ira A. Fulton Schools of Engineering at Arizona State University, is developing a called OncoMerge that uses genetic data to improve cancer modeling technology.