Loretta Marie Perera’s picture

By: Loretta Marie Perera

Recently, the team at 4C Creative Cad CAM Consultants in Emmen, Netherlands, was given a unique task: How to get a vintage Harley Davidson motorcycle back on the road again.

What was fun about this project wasn’t how challenging it was, or how much expertise it required. The joy was in the end itself, to provide a straightforward solution to a question that had been on the mind of one man for decades: How to get his vintage motorcycle capable of starting and riding on the streets. The solution was to scan a broken part that could no longer be found and 3D print a replacement.

The problem was brought to Carl van de Rijzen of Visual First in the Netherlands, who has been working with Edwin Rappard of 4C Creative CAD CAM Consultants for more than two years. Living on opposite ends of the country, the two have never met in person. “I send something to Edwin, he scans it and sends it back,” says van de Rijzen. The same thing occurred in this case.

Kate Saenko’s picture

By: Kate Saenko

Last month, Google forced out a prominent AI ethics researcher after she voiced frustration with the company for making her withdraw a research paper. The paper pointed out the risks of language-processing artificial intelligence, the type used in Google Search and other text analysis products.

Among the risks is the large carbon footprint of developing this kind of AI technology. By some estimates, training an AI model generates as much carbon emissions as it takes to build and drive five cars over their lifetimes.

I am a researcher who studies and develops AI models, and I am all too familiar with the skyrocketing energy and financial costs of AI research. Why have AI models become so power hungry, and how are they different from traditional data center computation?

NordVPN Teams’s picture

By: NordVPN Teams

According to Gartner, 99 percent of the vulnerabilities exploited in 2020 have been ones known about by security and IT professionals at the time of the incident. However, taking care of them is tiresome, as it takes 38 days to implement a patch and in the past year alone 12,174 new common vulnerabilities and exposures (CVEs) were reported.

Software vendors are constantly publishing patches to fix identified problems, but the users themselves are responsible for the updates. Failing to install them leaves the back door open for cyber criminals who can utilize it for a breach.

NVision Inc.’s picture

By: NVision Inc.

NVision’s engineering services are helping managers of coal-fired power plants converting to natural gas to determine more quickly where to install updated instrumentation necessary to retrofit turbines to accommodate the new power source.

“By measuring the equipment via laser scanning, then creating precise 3D models of the turbine assemblies for engineers to analyze for optimal installation points, we can significantly expedite the plants’ transitions,” says Steve Kersen, president of NVision. “This can result in huge cost savings for projects that would otherwise have been budgeted for a lengthier period using less sophisticated measurement methods. In one recent project, a Southeast power plant converting to a combined-cycle gas turbine (CCGT*) system will increase wattage output by more than 30 percent and save more than $250,000 by using our services.”

Douglas Allen’s picture

By: Douglas Allen

Any number derived from real observation is made up of three components. The first of these is the intended signal, the “perfect” value from the object being observed. The second is error (or noise) caused by environmental disturbance and/or interference. The third is bias, a regular and consistent deviation from the perfect value.

O = S + N + B, or observation equals signal plus noise plus bias

The signal usually is predictably constant, as is the bias. Identifying and eliminating bias requires a set of techniques beyond the scope of this article, so for the remainder of this, we will consider both as components of the signal, leaving a somewhat simpler equation for our observation.

O = S + N, or observation equals signal plus noise

This article focuses on removing the random noise component from the observation and leaving the signal component. The noise is in the form of chance variation, which sometimes enhances the signal and sometimes detracts from it. If we could separate the noise from the signal and eliminate it, our observation would be pure signal, or a precise and consistent value.

Alena Komaromi’s picture

By: Alena Komaromi

When your own inbox is overflowing with unread messages, it may not seem like the best tactic, but with the right approach, email can be a powerful negotiation tool, not least in the B2B realm. According to 2019 research by IACCM, a global contract management association, about 75 percent of contract negotiations are completely virtual. 

Nowadays, many B2B sales negotiations involve an open-bid process with a standardized communication where relationship bonds are less important. In that context, emails offer a number of advantages. For instance, they can be instantly accessed, often by many parties in an organization, thus creating transparency. Emails also allow a rich diversity of materials to be used as attachments.

Negotiations via email can be particularly suitable when gender, age, or racial biases—or linguistic issues such as a strong accent—could mar the process. It can also help when there is a power distance between parties, or when some voices risk being unheard.

Manufacturing USA’s picture

By: Manufacturing USA

The future of advanced manufacturing in the United States is being built at innovative facilities that enable experimentation in process and product development. The people and organizations at these next-generation facilities are part of a collaborative effort to remove barriers of entry and create an ecosystem to build supply chains and provide a path for the commercialization of emerging technologies.

These facilities are working on initiatives that include:
• Using advanced fiber technology to make programmable backpacks that have no wires or batteries but connect to the digital world.
• Using light instead of electronics to power cloud-based data centers, increasing the speed of transfer tenfold while drastically reducing energy use and cost.
• Extending the range of electric vehicles by reducing weight and mitigating energy loss during transfers.

This would not be possible without Manufacturing USA, a network of 16 manufacturing innovation institutes and their sponsoring federal agencies—the Departments of Commerce, Defense, and Energy. Manufacturing USA was created in 2014 to secure U.S. global leadership in advanced manufacturing by connecting people, ideas, and technology.

Rachel Gordon’s picture

By: Rachel Gordon

First published Dec. 7, 2020, on MIT Computer Science & Artificial Intelligence Lab (CSAIL) news.

In a classic experiment on human social intelligence by Warneken and Tomasello, an 18-month-old toddler watches a man carry a stack of books toward an unopened cabinet. When the man reaches the cabinet, he clumsily bangs the books against the door of the cabinet several times, then makes a puzzled noise.

Something remarkable happens next: The toddler offers to help. Having inferred the man’s goal, the toddler walks up to the cabinet and opens its doors, allowing the man to place his books inside. But how is the toddler, with such limited life experience, able to make this inference?

Recently, computer scientists have redirected this question toward computers: How can machines do the same?

Lawrence Livermore National Laboratory’s picture

By: Lawrence Livermore National Laboratory

A team of Lawrence Livermore National Laboratory (LLNL) scientists has simulated the droplet-ejection process in an emerging metal 3D-printing technique called “liquid metal jetting” (LMJ), a critical aspect to the continued advancement of liquid metal printing technologies.

In their paper, which was published in the journal Physics of Fluids, the team describes the simulating of metal droplets during LMJ, a novel process in which molten droplets of liquid metal are jetted from a nozzle to 3D-print a part in layers. The process does not require lasers or metal powder and is more similar to inkjet printing techniques.

Using the model, researchers studied the primary breakup dynamics of the metal droplets, essential to improving the understanding of LMJ. LMJ has advantages over powder-based approaches in that it provides a wider material set and does not require production or handling of potentially hazardous powders, researchers said.

Multiple Authors
By: Matthew Hutson, Knowable Magazine

This story was originally published by Knowable Magazine.

When Stefanie Tellex was 10 or 12, around 1990, she learned to program. Her great-aunt had given her instructional books, and she would type code into her father’s desktop computer. One program she typed in was a famous artificial intelligence program called ELIZA, which aped a psychotherapist. Tellex would tap out questions, and ELIZA would respond with formulaic text answers.

“I was just fascinated with the idea that a computer could talk to you, that a computer could be alive, like a person is alive,” Tellex says. Even ELIZA’s rote answers gave her a glimmer of what might be possible.

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