Ossi Oikarinen: At the Races

At Grand Prix race courses all over the globe, he tunes sleek, high-powered Formula 1 race cars for flawless performance

4 min read
Ossi Oikarinen
Fast Times: Race engineer Ossi Oikarinen travels the world keeping his Formula 1 race cars in perfect running order.
Photo: Paulo Fridman

On a warm October afternoon, dozens of the fastest and most advanced automobiles in the world are tearing up the Interlagos Race Track just south of São Paulo, Brazil. The high-pitched screams of the race cars are deafening as they run through practice laps on the twisty, hilly, 4.3-kilometer course, with its 15 turns and views of suburban high-rise apartment buildings in the distance.

With just two days to go before the Brazilian Formula 1 Grand Prix, the drivers are getting familiar with the course. And behind the scenes, but no less significant, the engineers are checking and tuning the countless vehicle technologies that will have to perform flawlessly over the 90 minutes of the race. The engineers are clustered in the pit area, and one of them, a blond Finn with a boyish face hardened into a studious glare, is watching real-time data flowing from one of the more than 80 sensors onboard his team’s car to a bank of computers and monitors in the pit. He is , race engineer for one of the three cars in the Panasonic Toyota Racing team, based in Cologne, Germany.

Keep reading...Show less

This article is for IEEE members only. Join IEEE to access our full archive.

Join the world’s largest professional organization devoted to engineering and applied sciences and get access to all of Spectrum’s articles, podcasts, and special reports. Learn more →

If you're already an IEEE member, please sign in to continue reading.

Membership includes:

  • Get unlimited access to IEEE Spectrum content
  • Follow your favorite topics to create a personalized feed of IEEE Spectrum content
  • Save Spectrum articles to read later
  • Network with other technology professionals
  • Establish a professional profile
  • Create a group to share and collaborate on projects
  • Discover IEEE events and activities
  • Join and participate in discussions

New AI Speeds Computer Graphics by Up to 5x

Neural rendering harnesses machine learning to paint pixels

5 min read
Four examples of Nvidia's Instant NeRF 2D-to-3D machine learning model placed side-by-side.

Nvidia Instant NeRF uses neural rendering to generate 3D visuals from 2D images.


On 20 September, Nvidia’s Vice President of Applied Deep Learning, Bryan Cantanzaro, went to Twitter with a bold claim: In certain GPU-heavy games, like the classic first-person platformer Portal, seven out of eight pixels on the screen are generated by a new machine-learning algorithm. That’s enough, he said, to accelerate rendering by up to 5x.

This impressive feat is currently limited to a few dozen 3D games, but it’s a hint at the gains neural rendering will soon deliver. The technique will unlock new potential in everyday consumer electronics.

Keep Reading ↓Show less

Golf Robot Learns To Putt Like A Pro

Watch out Tiger Woods, Golfi has a mean short game

4 min read
Golf Robot Learns To Putt Like A Pro

While being able to drive the ball 300 yards might get the fans excited, a solid putting game is often what separates a golf champion from the journeymen. A robot built by German researchers is quickly becoming a master of this short game using a clever combination of classical control engineering and machine learning.

In golf tournaments, players often scout out the greens the day beforehand to think through how they are going to play their shots, says Annika Junker, a doctoral student at Paderborn University in Germany. So she and her colleagues decided to see if giving a robot similar capabilities could help it to sink a putt from anywhere on the green, without assistance from a human.

Keep Reading ↓Show less

Solving Automotive Design Challenges With Simulation

Learn about low-frequency electromagnetic simulations and see a live demonstration of COMSOL Multiphysics software

1 min read

The development of new hybrid and battery electric vehicles introduces numerous design challenges. Many of these challenges are static or low-frequency electromagnetic by nature, as the devices involved in such designs are much smaller than the operating wavelength. Examples include sensors (such as MEMS sensors), transformers, and motors. Many of these challenges include multiple physics. For instance, sensors activated by acoustic energy as well as heat transfer in electric motors and power electronics combine low-frequency electromagnetic simulations with acoustic and heat transfer simulations, respectively.

Multiphysics simulation makes it possible to account for such phenomena in designs and can provide design engineers with the tools needed for developing products more effectively and optimizing device performance.

Keep Reading ↓Show less