Lifeboat Foundation

501 likes, — growasentrepreneurs on September 13, 2024: Nvidia’s Blackwell chip is an engineering marvel, crafted from two of the largest chips ever made using TSMC’s 4-nanometer process. It took $10 billion and 3 years to develop, supported by high-speed networking, software, and incredible I/O capabilities.

This chip powers AI factories in data centers, designed to emulate human intelligence—specifically how we read, finish sentences, and summarize information.

Jensen Huang compares it to the intelligence of thousands of people, showcasing Blackwell’s potential to revolutionize AI in an unprecedented way.

It takes years of intense study and a steady hand for humans to perform surgery, but robots might have an easier time picking it up with today’s AI technology.

Researchers at Johns Hopkins University (JHU) and Stanford University have taught a robot surgical system to perform a bunch of surgical tasks as capably as human doctors, simply by training it on videos of those procedures.

Continue reading “Robot learns to perform surgical tasks expertly just by watching videos” »

Baidu has introduced a pair of smart glasses powered by its ERNIE AI assistant.

Now, scientists have not only cooled muons but also accelerated them in an experiment at the Japan Proton Accelerator Research Complex, or J-PARC, in Tokai. The muons reached a speed of about 4 percent the speed of light, or roughly 12,000 kilometers per second, researchers report October 15 at arXiv.org.

The scientists first sent the muons into an aerogel, a lightweight material that slowed the muons and created muonium, an atomlike combination of a positively charged muon and a negatively charged electron. Next, a laser stripped away the electrons, leaving behind cooled muons that electromagnetic fields then accelerated.

Muon colliders could generate higher energy collisions than machines that smash protons, which are themselves made up of smaller particles called quarks. Each proton’s energy is divvied up among its quarks, meaning only part of the energy goes into the collision. Muons have no smaller bits inside. And they’re preferable to electrons, which lose energy as they circle an accelerator. Muons aren’t as affected by that issue thanks to their larger mass.

Amazon is poised to roll out its newest artificial intelligence chips as the Big Tech group seeks returns on its multibillion-dollar semiconductor investments and to reduce its reliance on market leader Nvidia.

Executives at Amazon’s cloud computing division are spending big on custom chips in the hopes of boosting the efficiency inside its dozens of data centers, ultimately bringing down its own costs as well as those of Amazon Web Services’ customers.

The effort is spearheaded by Annapurna Labs, an Austin-based chip start-up that Amazon acquired in early 2015 for $350 million. Annapurna’s latest work is expected to be showcased next month when Amazon announces widespread availability of ‘Trainium 2,’ part of a line of AI chips aimed at training the largest models.

A new computational method can identify how cause-and-effect relationships ebb and flow over time in dynamic real-life systems such as the brain.

An international research team has for the first time designed realistic photonic time crystals–exotic materials that exponentially amplify light. The breakthrough opens up exciting possibilities across fields such as communication, imaging and sensing by laying the foundations for faster and more compact lasers, sensors and other optical devices.

“For an existing barrel roof stadium, renovating the opening will be a good solution. Reworking the roof will be much costlier,” Jayanarasimhan explained.

Jayanarasimhan hopes these findings will help the sports community realize that there are better solutions for mitigating wind drift beyond just turning off the ventilation.

“We expect that with this pace of research down the road, wind drift complaints will be negligible from badminton tournaments,” said Jayanarasimhan. “We are preparing to study other roof configurations [and] the deviation of the shuttlecock trajectory in different wind directions and conduct a case study of the existing indoor badminton stadiums.”

A team of AI researchers and mathematicians affiliated with several institutions in the U.S. and the U.K. has developed a math benchmark that allows scientists to test the ability of AI systems to solve exceptionally difficult math problems. Their paper is posted on the arXiv preprint server.