A new computer vision system inspired by cats’ eyes could enable robots to see the world around them more accurately than ever before.
Robots, drones, self-driving cars and other autonomous systems are becoming more common, but they still struggle to see well in all environments and conditions. For example, self-driving cars perform poorly in rain or fog because these conditions affect the car’s sensors and cameras.
This clip is from the following episode: https://youtu.be/xqS5PDYbTsE
Recorded on Oct 18th, 2024
Views are my own thoughts; not Financial, Medical, or Legal Advice.
In this episode, Ray and Peter discuss 2025 predictions, Job loss in the coming years, and Ray’s thoughts on nanotech taking over the world.
Ray Kurzweil is a world-class inventor, thinker, and futurist, with a thirty-five-year track record of accurate predictions. He has been a leading developer in artificial intelligence for 61 years – longer than any other living person. He was the principal inventor of the first CCD flat-bed scanner, omni-font optical character recognition, print-to-speech reading machine for the blind, text-to-speech synthesizer, music synthesizer capable of recreating the grand piano and other orchestral instruments, and commercially marketed large-vocabulary speech recognition software. Ray received a Grammy Award for outstanding achievement in music technology; he is the recipient of the National Medal of Technology, was inducted into the National Inventors Hall of Fame, and holds twenty-one honorary Doctorates. He has written five best-selling books including The Singularity Is Near and How To Create A Mind, both New York Times bestsellers, and Danielle: Chronicles of a Superheroine, winner of multiple young adult fiction awards. His new book, The Singularity Is Nearer was released on June 25th and debuted at #4 on the New York Times Best Seller list. He is a Principal Researcher and AI Visionary at Google.
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By analyzing the resistance genes and proteins of E. coli, researchers can optimize treatments to address both current and future antimicrobial resistance.
Generative AI is changing medicine, and it’s happening fast. HMS is getting a jump on this shift by training future doctors with skills in data and machine learning.
Harvard Medical School is building artificial intelligence into the curriculum to train the next generation of doctors.
Today, more than a quarter of all new code at Google is generated by AI, then reviewed and accepted by engineers.
More than a quarter of Google’s new code is being generated by artificial intelligence (AI), CEO Sundar Pichai revealed during Tuesday’s third-quarter earnings call for the leading tech company.
We’re also using AI internally to improve our coding processes, which is boosting productivity and efficiency, Pichai said during the call.
This was first reported by the Wall Street Journal. This comes after the company recently received a fundraise of $6 billion in a Series B round. The company said in a statement that the funding saw participation from several key investors, including Valor Equity Partners, Vy Capital, Andreessen Horowitz, Sequoia Capital, Fidelity Management & Research Company, Prince Alwaleed Bin Talal, Kingdom Holding, and others.
“Al-determined tumor volume has the potential to advance precision medicine for patients with prostate cancer by improving our ability to understand the aggressiveness of a patient’s cancer and therefore recommend the most optimal treatment,” said Dr. David D. Yang, MD.
How can artificial intelligence (AI) help medical professionals identify, diagnose, and treat prostate cancer? This is what a recent study published in Radiology hopes to address as a team of researchers developed an AI model designed to identify prostate cancer lesions, which holds the potential to help medical professionals and patients make the best-informed decisions regarding diagnoses and treatment options.
For the study, which was conducted between January 2021 to August 2023, the researchers had their AI model examine MRI scans from 732 patients, including 438 patients who underwent radiation therapy (RT) and 294 patients who underwent radical prostatectomy (RP). The goal was to compare a potential success rate of the AI model identifying tumors compared to patient treatment between 5 to 10 years after being diagnosed.
In the end, the AI model demonstrated an 85 percent accuracy in identifying cancerous lesions. Additionally, the AI model identified the larger volume lesions that resulted in failed treatment and metastasis, which is when cancer tumors spread beyond the original location within the body. Finally, the AI model determined that RT patients were at a decreased risk of metastasis based on their tumor volumes.
Reuters reports an updated hardware strategy to run ChatGPT and OpenAI’s other projects involves using AMD chips via Microsoft Azure in addition to Nvidia.
This level of precision could be a game-changer for therapies that require gene expression in one specific tissue, without impacting others.
By providing more control over where and when genes are activated, these AI-designed CREs could potentially be used in a variety of therapeutic applications, from treating genetic diseases to optimizing tissue regeneration.
As this AI-powered approach to designing CREs matures, the possibilities are vast. Beyond basic research, these synthetic DNA switches could be employed in biomanufacturing or to develop advanced treatments for a range of conditions, offering more effective ways to manipulate genes with unprecedented precision.
Caltech scientists have introduced a revolutionary machine-learning-driven technique for accurately measuring the mass of individual particles using advanced nanoscale devices.
This method could dramatically enhance our understanding of proteomes by allowing for the mass measurement of proteins in their native forms, thus offering new insights into biological processes and disease mechanisms.
Caltech scientists have developed a machine-learning-powered method that enables precise measurement of individual particles and molecules using advanced nanoscale devices. This breakthrough could lead to the use of various devices for mass measurement, which is key to identifying proteins. It also holds the potential to map the complete proteome—the full set of proteins in an organism.
