Google's new AI podcasting tool, called Audio Overview, has become a surprise viral hit. The podcasting feature was launched in mid-September as part of NotebookLM, a year-old AI-powered research assistant. NotebookLM, which is powered by Google's Gemini 1.5 model, allows people to upload content such as links, videos, PDFs, and text. They can then ask the system questions about the content, and it offers short summaries. The tool generates a podcast called Deep Dive, which features a male and a female voice discussing whatever you uploaded.

Surfers, swimmers and beachgoers face a hidden danger in the ocean: rip currents. These narrow channels of water can flow away from the shore at speeds up to 2.5 meters per second, making them one of the biggest safety risks for those enjoying the ocean. To help keep beachgoers safe, Christo Rautenbach, a coastal and estuarine physical processes scientist, has teamed up with the National Institute of Water and Atmospheric Research in New Zealand to develop a real-time rip current identification tool using deep learning. On this episode of the NVIDIA AI Podcast, host Noah Kravitz interviews Rautenbach about how AI can be used to identify rip currents and the potential for the tool to be used globally to help reduce the number of fatalities caused by rip currents. Developed in collaboration with Surf Lifesaving New Zealand, the rip current identification tool has achieved a detection rate of roughly 90% in trials.

A renowned expert in machine learning, Urtasun discusses her current work at Waabi using simulation technology to teach trucks how to drive.

Training, testing and validating autonomous vehicles requires a continuous pipeline -- or data factory -- to introduce new scenarios and refine deep neural networks. A key component of this process is simulation. AV developers can test a virtually limitless number of scenarios, repeatably and at scale, with high-fidelity, physically based simulation. And like much of the technology related to AI, simulation is constantly evolving and improving, getting ever nearer to closing the gap between the real and virtual worlds. NVIDIA DRIVE Sim, built on Omniverse, provides a virtual proving ground for AV testing and validation.

Living With AI Podcast: Challenges of Living with Artificial Intelligence By Sean Riley Download from Itunes

With the vast amounts of research and development occurring every day in Machine Learning, it can be challenging for industry professionals solving real-life use-cases and academic researchers to keep up with all the recent innovations in their specific field of interest. Having struggled for a long time, after a series of exploration, I finally stumbled upon a handful of resources that I wish to share in this post. The list I am proposing here is not exhaustive. However, I am sure they will be sufficient to keep you updated-- eliminating all the heavy lifting of scanning the list of published papers yourself. The resources I will discuss in this post encompass video, newsletter, and podcast formats.

I've at all times been fascinated by expertise and am nonetheless attempting to wrap my head round a few of the use-cases we now have seen for AI in the previous few years. Be it the self-driving vehicles, the primary AI beating a human at Alpha Go, or the information about two Google AIs interacting with one another and forming their very own language utilizing English phrases. All these situations present us how far we have come when it comes to expertise, and but we have simply begun. So when you're somebody as intrigued with these applied sciences and need to sustain with the most recent developments in AI, ML, and Information Science, I've acquired one thing only for you! Listed below are the highest 10 podcasts on synthetic intelligence in 2022.

It may seem intuitive that AI and deep learning can speed up workflows -- including novel drug discovery, a typically years-long and several-billion-dollar endeavor. But professors Artem Cherkasov and Olexandr Isayev were surprised to find that no recent academic papers provided a comprehensive, global research review of how deep learning and GPU-accelerated computing impact drug discovery. In March, they published a paper in Nature to fill this gap, presenting an up-to-date review of the state of the art for GPU-accelerated drug discovery techniques. Cherkasov, a professor in the department of urologic sciences at the University of British Columbia, and Isayev, an assistant professor of chemistry at Carnegie Mellon University, join NVIDIA AI Podcast host Noah Kravitz this week to discuss how GPUs can help democratize drug discovery. In addition, the guests cover their inspiration and process for writing the paper, talk about NVIDIA technologies that are transforming the role of AI in drug discovery, and give tips for adopting new approaches to research.

Entrepreneur Jason Mars calls conversation our "first technology." Before humans invented the wheel, crafted a spear or tamed fire, we mastered the superpower of talking to one another. That makes conversation an incredibly important tool. But if you've dealt with the automated chatbots deployed by the customer service arms of just about any big organization lately -- whether banks or airlines -- you also know how hard it can be to get it right. Deep learning AI and new techniques such as zero-shot learning promise to change that.

What John Madden was to pro football, Neda Cvijetic is to autonomous vehicles. Cvijetic, senior manager of autonomous vehicles at NVIDIA, drives our NVIDIA DRIVE Labs series of videos and blogs breaking down the science behind autonomous vehicles. A Serbian-American electrical engineer, Cvijetic seems destined for this role. She literally grew up in the shadow of Nikola Tesla. His statue in Belgrade stood across the street from her childhood home.