Lifeboat Foundation

Just like Taylor Swift’s wildly successful Eras tour, Nvidia has taken center stage in their own widely successful AI Era tour. From Wall Street to Main Street, everyone is talking about Nvidia, and rightfully so. By powering the latest innovations in AI, Nvidia has achieved 126% revenue growth and 286% net income growth in the past fiscal year, an achievement most companies can only dream about, to become one of the most world’s most valuable companies. All of this is a result of being able to take existing core competencies like their GPU expertise and successfully applying it to an adjacent, yet still emerging use case like artificial intelligence (AI).

Much of Nvidia’s success can be attributed to one of its founders and the only CEO the company has ever had, Jensen Huang. Mr. Huang was recently recognized as one of the world’s most accomplished engineers with his election to the National Academy of Engineering (NAE), a nonprofit organization with more than 2,000 peer-elected members from industry, academia, and government that “provides engineering leadership in service to the nation.” This is a huge career achievement, one of the highest professional distinctions possible for an engineer.

Mr. Huang likes to say that “Nvidia innovates at the speed of light.” To his credit, Mr. Huang has continued to drive this kind of innovation at Nvidia since its inception. Nvidia was one of many companies developing graphics in the early days of PC gaming and one of the few to survive. Nvidia pioneered the Graphics Processing Unit (GPU) and was the first company to promote the concept of using GPUs for general computing purposes, which became known as GPGPU compute and led to the development of the Compute Unified Device Architecture (CUDA) software framework aimed at fully utilizing the massively parallel processing capabilities of Nvidia GPUs. With the advent of deep-learning techniques to train neural network models, Nvidia quickly adapted both its hardware and software solutions to enable an exponential growth in processing capabilities that led to the traditional and generative AI innovations that are sweeping the world today.

Learn about the incredible capabilities of Cerebras Systems’ new AI chip, the Wafer Scale Engine (WSE-3), with four trillion transistors.

A new research in battery technology now promises safer, longer-lasting energy storage. Thanks to a research team tackling a critical issue with solid-state batteries. The researchers have now developed a “bottom electrodeposition” method that changes the game for these next-generation power sources.

Today’s batteries say the ones in our smartphones or electric cars, mostly use liquid electrolytes for shuttling energy. However, these liquids are flammable, which obviously factors into safety concerns, even though they are minimal in today’s modern processes.

Learn more about neural networks on Brilliant! First 30 days are free and the first 200 to use our link ➜ https://brilliant.org/sabine will get 20% off the annual premium subscription.

Some major news outlets are about to release a feature known as “Content Credentials” to try and combat the spread of deepfakes. What are “Content Credentials”? Will it really stop deepfakes of Biden and Trump dancing together from spreading? Let’s have a look.

Continue reading “Credentials against Deepfakes: How will it work?” »

Hello friends, Welcome back to another episode of Engineer…

The calculation, which took around 75 days to complete, was carried out with 36 of the company’s proprietary solid-state drives (SSDs) — a storage medium fitted into many of the newest laptops — that stored altogether around 1 petabyte (1 million gigabytes) of data.

Processors are also needed to perform the number-crunching — with more powerful components reducing the time it takes to perform the necessary calculations. However, reliable and large-capacity storage is arguably more important because you need to store a massive amount of data in such a process.

The achievement “was no small feat,” Solidigm owner Brian Beeler said in the statement. “It involved meticulous planning, optimization, and execution.”

Wired writer Mark Andrews tested three Chinese vehicles equipped with semi-autonomous functionality and found them superior to comparable American self-driving systems. The reasons, it seems, boil down to a single feature that American passenger cars have yet to implement: Lidar. From Wired:

On the flip side, Tesla and General Motors have been grabbing most of the recent headlines when it comes to self-driving cars in the hands of the public, and for all the wrong reasons—mass recalls, suspended licenses, spending cuts, and huge losses.

But in China, a number of companies are steadily—and far more successfully—moving toward a similar destination, but via a different route.

People often think of leprosy as a bygone disease, relevant primarily in biblical times. But in fact, it is still present in more than 120 countries, and the US is seeing an uptick in cases.

GPT and Dall-e are just the first baby steps in the world of human-like AI.