What security does a default OpenBSD installation offer? (by solene@)

In a recent blog post, OpenBSD developer Solène Rapenne (solene@) offers an over view of the security features offered by a default OpenBSD installation.

The first paragraph of the introduction reads,

In this text I will explain what makes OpenBSD secure by default when you install it. Do not take this for a security analysis, but more like a guide to help you understand what is done by OpenBSD to have a secure environment. The purpose of this text is not to compare OpenBSD to other OSes but to say what you can honestly expect from OpenBSD.

A worthy reminder of how the system works, and a very handy piece to show to anybody who wonders why one would choose to use OpenBSD over anything else. You can read the whole thing here.

dhcpleased(8) – DHCP client daemon

With the following commit, Florian Obser (florian@) imported dhcpleased(8), DHCP daemon to acquire IPv4 address leases from servers, plus dhcpleasectl(8), a utility to control the daemon:

CVSROOT:	/cvs
Module name:	src
Changes by:	florian@cvs.openbsd.org	2021/02/26 09:16:37

Added files:
	sbin/dhcpleased: Makefile bpf.c bpf.h checksum.c checksum.h 
	                 control.c control.h dhcpleased.8 dhcpleased.c 
	                 dhcpleased.h engine.c engine.h frontend.c 
	                 frontend.h log.c log.h 
	usr.sbin/dhcpleasectl: Makefile dhcpleasectl.8 dhcpleasectl.c 
	                       parser.c parser.h 

Log message:
Import dhcpleased(8) - a dhcp daemon to acquire IPv4 address leases
from servers.

Read more…

Meet the Maker: DIY Builder Takes AI to Bat for Calling Balls and Strikes

Baseball players have to think fast when batting against blurry-fast pitches. Now, AI might be able to assist. Nick Bild, a Florida-based software engineer, has created an application that can signal to batters whether pitches are going to be balls or strikes. Dubbed Tipper, it can be fitted on the outer edge of glasses to Read article >

The post Meet the Maker: DIY Builder Takes AI to Bat for Calling Balls and Strikes appeared first on The Official NVIDIA Blog.

Meet the Maker: DIY Builder Takes AI to Bat for Calling Balls and Strikes

Baseball players have to think fast when batting against blurry-fast pitches. Now, AI might be able to assist.

Nick Bild, a Florida-based software engineer, has created an application that can signal to batters whether pitches are going to be balls or strikes. Dubbed Tipper, it can be fitted on the outer edge of glasses to show a green light for a strike or a red light for a ball.

Tipper uses image classification to alert the batter before the ball has traveled halfway to home plate. It relies on the NVIDIA Jetson edge AI platform for split-second inference, which triggers the lights.

He figures his application could be used to help as a training aid for batters to help recognize good pitches from bad. Pitchers also could use it to analyze whether any body language tips off batters on their delivery.

“Who knows, maybe umpires could rely on it. For those close calls, it might help to reduce arguments with coaches as well as the ire of fans,” said Bild.

About the Maker

Bild works in the telecom industry by day. By night, he turns his living room into a laboratory for Jetson experiments.

And Bild certainly knows how to have fun. And we’re not just talking about his living room-turned-batting cage. Self-taught on machine learning, Bild has applied his ML and Python chops to Jetson AGX Xavier for projects like ShAIdes, enabling gestures to turn on home lights.

Bild says machine learning is particularly useful to solve problems that are otherwise unapproachable. And for a hobbyist, he says, the cost of entry can also be prohibitively high.

His Inspiration

When Bild first heard about Jetson Nano, he saw it as a tool to bring his ideas to life on a small budget. He bought one the day it was first released and has been building devices with it ever since.

The first Jetson project he created was called DOOM Air. He learned image classification basics and put that to work to operate a computer that was projecting the blockbuster video game DOOM onto the wall, controlling the game with his body movements.

Jetson’s ease of use enabled early successes for Bild, encouraging him to take on more difficult projects, he says.

“The knowledge I picked up from building these projects gave me the basic skills I needed for a more elaborate build like Tipper,” he said.

His Favorite Jetson Projects

Bild likes many of his Jetson projects. His Deep Clean project is one favorite. It uses AI to track the places in a room touched by a person so that it can be sanitized.

But Tipper is Bild’s favorite Jetson project of all. Its pitch predictions are aided by a camera that can capture 100 frames per second. Facing the camera at the ball launcher — a Nerf gun —  it can capture two successive images of the ball early in flight.

Tipper was trained on “hundreds of images” of balls and strikes, he said. The result is that Jetson AGX Xavier classifies balls in the air to guide batters better than a first base coach.

As far as fun DIY AI, this one is a home run.

The post Meet the Maker: DIY Builder Takes AI to Bat for Calling Balls and Strikes appeared first on The Official NVIDIA Blog.

What Is Cloud Gaming?

Cloud gaming uses powerful, industrial-strength GPUs inside secure data centers to stream your favorite games over the internet to you. So you can play the latest games on nearly any device, even ones that can’t normally play that game. But First, What Is Cloud Gaming? While the technology is complex, the concept is simple. Cloud Read article >

The post What Is Cloud Gaming? appeared first on The Official NVIDIA Blog.

What Is Cloud Gaming?

Cloud gaming uses powerful, industrial-strength GPUs inside secure data centers to stream your favorite games over the internet to you. So you can play the latest games on nearly any device, even ones that can’t normally play that game.

But First, What Is Cloud Gaming?

While the technology is complex, the concept is simple.

Cloud gaming takes your favorite game, and instead of using the device in front of you to power it, a server — a powerful, industrial-strength PC — runs the game from a secure data center.

Gameplay is then streamed over the internet back to you, allowing you to play the latest games on nearly any device, even ones that are not capable of running can’t actually play that game.

Cloud gaming streams the latest games from powerful GPUs in remote data centers to nearly any device.

Video games are interactive, obviously. So, cloud gaming servers need to process information and render frames in real time. Unlike movies or TV shows that can provide a buffer — a few extra seconds of information that gets sent to your device before it’s time to be displayed — games are dependent on the user’s next keystroke or button press.

Introducing GeForce NOW

We started our journey to cloud gaming over 10 years ago, spending that time to optimize every millisecond of the pipeline that we manage, from the graphics cards in the data centers to the software on your local device.

Here’s how it works.

GeForce NOW is a service that takes a GeForce gaming PC’s power and flexibility and makes it accessible through the cloud. This gives you an always-on gaming rig that never needs upgrading, patching or updating — across all of your devices.

One of the things that makes GeForce NOW unique is that it connects to popular PC games stores — Steam, Epic Games Store, Ubisoft Connect and more — so gamers can play the same PC version of games their friends are playing.

It also means, if they already own a bunch of games, they can log in and start playing them. And if they have, or upgrade to, a gaming rig, they have access to download and play those games on that local PC.

GeForce NOW empowers you to take your PC games with you, wherever you go.

Gamers get an immersive PC gaming experience, instant access to the world’s most popular games and gaming communities, and the freedom to play on any device, at any time.

It’s PC gaming for those whose PCs have integrated graphics, for Macs and Chromebooks that don’t have access to the latest games, or for internet-connected mobile devices where PC gaming is only a dream.

Over 80 percent of GeForce NOW members are playing on devices that don’t meet the min spec for the games they’re playing.

To start, sign up for the service, download the app and begin your cloud gaming journey.

Powering PC Gaming from the Cloud

Cloud data centers with NVIDIA GPUs power the world’s most computationally complex tasks, from AI to data analytics and research. Combined with advanced GeForce PC gaming technologies, GeForce NOW delivers high-end PC gaming to passionate gamers.

NVIDIA RTX servers provide the backbone for GeForce NOW.

GeForce NOW data centers include NVIDIA RTX servers that feature RTX GPUs. These GPUs enable the holy grail of modern graphics: real-time ray tracing, and DLSS, NVIDIA’s groundbreaking AI rendering that boosts frame rates for uncompromised image quality. The hardware is supported with NVIDIA Game Ready Driver performance improvements.

Patented encoding technology — along with hardware acceleration in both video encoding and decoding, pioneered by NVIDIA more than a decade ago — allows for gameplay to be streamed at high frame rates, with low enough latency that most games will feel like the game is being played locally. Gameplay rendered in GeForce NOW data centers is converted into high-definition H.265 and H.264 video and streamed back to the gamer instantaneously.

The total time it takes from button press or keystroke to the action appearing on the screen is less than one-tenth of a second, faster than the blink of an eye.

Growing Cloud Gaming Around the World

With the ambition to deliver quality cloud gaming to all gamers, NVIDIA works with partners around the world including telecommunications and service providers to put GeForce NOW servers to work in their own data centers, ensuring lightning-fast connections.

Partners that have already deployed RTX cloud gaming servers include SoftBank and KDDI in Japan, LG Uplus in Korea, GFN.RU in Russia, Armenia, Azerbaijan, Belarus, Kazakhstan, Georgia, Moldova, Ukraine and Uzbekistan, Zain in Saudi Arabia and Taiwan Mobile in Taiwan.

Together with partners from around the globe, we’re scaling GeForce NOW to enable millions of gamers to play their favorite games, when and where they want.

Get started with your gaming adventures on GeForce NOW.

Editor’s note: This is the first in a series on the GeForce NOW game-streaming service, how it works, ways you can make the most of it, and where it’s going next. 

In our next blog, we’ll talk about how we bring your games to GeForce NOW.

Follow GeForce NOW on Facebook and Twitter and stay up to date on the latest features and game launches. 

The post What Is Cloud Gaming? appeared first on The Official NVIDIA Blog.

In the Drink of an AI: Startup Opseyes Instantly Analyzes Wastewater

Let’s be blunt. Potentially toxic waste is just about the last thing you want to get in the mail. And that’s just one of the opportunities for AI to make the business of analyzing wastewater better.

It’s an industry that goes far beyond just making sure water coming from traditional sewage plants is clean.

Just about every industry on earth — from computer chips to potato chips — relies on putting water to work, which means we’re all, literally, swimming in the stuff.

Just What the Doctor Ordered

That started to change, however, thanks to a conversation Opseyes founder Bryan Arndt, then a managing consultant with Denmark-based architecture and engineering firm Ramboll, had with his brother, a radiologist.

Arndt was intrigued when his brother described how deep learning was being set loose on medical images.

Arndt quickly realized that the same technology — deep learning — that helps radiologists analyze images of the human body faster and more accurately could almost instantly analyze images, taken through microscopes, of wastewater samples.

Faster Flow

The result, developed by Arndt and his colleagues at Ramboll, a wastewater industry leader for more than 50 years, dramatically speeds up an industry that’s long relied on sending tightly sealed samples of some of the stinkiest stuff on earth through the mail.

That’s critical when cities and towns and industries of all kinds are constantly taking water from lakes and rivers, like the Mississippi, treating it, and returning it to nature.

“We had one client find out their discharge was a quarter-mile, at best, from the intake for the next city’s water supply,” Arndt says. “Someone is always drinking what your tube is putting out.”

That makes wastewater enormously important.

Water, Water, Everywhere

It’s an industry that was kicked off by the 1972 U.S. Clean Water Act, a landmark not just in the United States, but globally.

Thanks to growing awareness of the importance of clean water, analysts estimate the global wastewater treatment market will be worth more than $210 billion by 2025.

The challenge: while almost every industry creates wastewater, wastewater expertise isn’t exactly ubiquitous.

Experts who can peer through a microscope and identify, say, the six most common bacterial “filaments” as they’re known in the industry, or critters such as tardigrades, are scarce.

You’ve Got … Ugh

That means samples of wastewater, or soil containing that water, have to be sent through the mail to get to these experts, who often have a backlog of samples to go through.

While Ardnt says people in his industry take precautions to seal potentially toxic waste and track it to ensure it gets to the right place, it’s still time-consuming.

The solution, Arndt realized, was to use deep learning to train an AI that could yield instantaneous results. To do this, last year Arndt reached out on social media to colleagues throughout the wastewater industry to send him samples.

Least Sexy Photoshoot Ever

He and his small team then spent months creating more than 6,000 images of these samples in Ramboll’s U.S. labs, where they build elaborate models of wastewater systems before deploying full-scale systems for clients. Think of it as the least sexy photoshoot, ever.

These images were then labeled and used by a data science  team lead by Robin Schlenga to train a convolutional neural network accelerated by NVIDIA GPUs. Launched last September after a year-and-a-half of development, Opseyes allows customers to use their smartphone to take a picture of a sample through a microscope and get answers within minutes.

It’s just another example of how expertise in companies seemingly far outside of tech can be transformed into an AI. After all, “no one wants to have to wait a week to know if it’s safe to take a sip of water,” Arndt says.

Bottoms up.

Featured image credit: Opseyes

The post In the Drink of an AI: Startup Opseyes Instantly Analyzes Wastewater appeared first on The Official NVIDIA Blog.

In the Drink of an AI: Startup Opseyes Instantly Analyzes Wastewater

Let’s be blunt. Potentially toxic waste is just about the last thing you want to get in the mail. And that’s just one of the opportunities for AI to make the business of analyzing wastewater better. It’s an industry that goes far beyond just making sure water coming from traditional sewage plants is clean. Just Read article >

The post In the Drink of an AI: Startup Opseyes Instantly Analyzes Wastewater appeared first on The Official NVIDIA Blog.

NVIDIA Deep Learning Institute Releases New Accelerated Data Science Teaching Kit for Educators

As data grows in volume, velocity and complexity, the field of data science is booming. There’s an ever-increasing demand for talent and skillsets to help design the best data science solutions. However, expertise that can help drive these breakthroughs requires students to have a foundation in various tools, programming languages, computing frameworks and libraries. That’s Read article >

The post NVIDIA Deep Learning Institute Releases New Accelerated Data Science Teaching Kit for Educators appeared first on The Official NVIDIA Blog.

NVIDIA Deep Learning Institute Releases New Accelerated Data Science Teaching Kit for Educators

As data grows in volume, velocity and complexity, the field of data science is booming.

There’s an ever-increasing demand for talent and skillsets to help design the best data science solutions. However, expertise that can help drive these breakthroughs requires students to have a foundation in various tools, programming languages, computing frameworks and libraries.

That’s why the NVIDIA Deep Learning Institute has released the first version of its Accelerated Data Science Teaching Kit for qualified educators. The kit has been co-developed with Polo Chau, from the Georgia Institute of Technology, and Xishuang Dong, from Prairie View A&M University, two highly regarded researchers and educators in the fields of data science and accelerating data analytics with GPUs.

“Data science unlocks the immense potential of data in solving societal challenges and large-scale complex problems across virtually every domain, from business, technology, science and engineering to healthcare, government and many more,” Chau said.

The free teaching materials cover fundamental and advanced topics in data collection and preprocessing, accelerated data science with RAPIDS, GPU-accelerated machine learning, data visualization and graph analytics.

Content also covers culturally responsive topics such as fairness and data bias, as well as challenges and important individuals from underrepresented groups.

This first release of the Accelerated Data Science Teaching Kit includes focused modules covering:

  • Introduction to Data Science and RAPIDS
  • Data Collection and Pre-processing (ETL)
  • Data Ethics and Bias in Data Sets
  • Data Integration and Analytics
  • Data Visualization
  • Distributed Computing with Hadoop, Hive, Spark and RAPIDS

More modules are planned for future releases.

All modules include lecture slides, lecture notes and quiz/exam problem sets, and most modules include hands-on labs with included datasets and sample solutions in Python and interactive Jupyter notebook formats. Lecture videos will be included for all modules in later releases.

DLI Teaching Kits also come bundled with free GPU resources in the form of Amazon Web Services credits for educators and their students, as well as free DLI online, self-paced courses and certificate opportunities.

“Data science is such an important field of study, not just because it touches every domain and vertical, but also because data science addresses important societal issues relating to gender, race, age and other ethical elements of humanity,“ said Dong, whose school is a Historically Black College/University.

This is the fourth teaching kit released by the DLI, as part of its program that has reached 7,000 qualified educators so far. Learn more about NVIDIA Teaching Kits.

The post NVIDIA Deep Learning Institute Releases New Accelerated Data Science Teaching Kit for Educators appeared first on The Official NVIDIA Blog.