The tech industry is contending with an incongruous reality: There’s both a talent shortage and a pervasive underrepresentation of women and people of color across teams and companies.

For many hiring and personnel experts, the status quo isn’t acceptable, and their organizations are working to change it. A few recently shared tips with Tech Brew about how companies that are innovating in their fields can help to create more diverse workplaces.

M.K. Palmore, director of Google Cloud’s office of the CISO, spent 22 years at the FBI before moving to the private sector. Now, he’s applying a forensic sensibility to improving Big Tech diversity practices.

Palmore started noticing the largely white, male monoculture at Silicon Valley tech companies when he worked as an FBI cybersecurity liaison. He said the relatively low numbers of women and people of color working in cybersecurity, compared to their representation in the general population, led him to a leadership role with Cyversity, a nonprofit working to bring people from underrepresented groups into the cybersecurity workforce.

According to Palmore, welcoming people from a variety of backgrounds into an organization starts at the early-career stage. To move toward a more diverse workforce, Palmore said that the industry should focus on creating more entry-level jobs, internship opportunities, and “trial runs” to help ensure new hires are a good fit.

“Organizations will say they want talent, and then you put talent in front of them, and the talent is missing something; they may have the certifications and degrees, but they don’t have the experience,” he said. “Because cybersecurity is such an impactful issue for business enterprise, oftentimes, there’s very little space or grace that’s given to the idea of hiring someone who may lack experience.”

Keep reading here.—KG

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Can AI predict the weather more quickly and accurately than the forecasting field’s top supercomputers?

That’s the contention of a new paper from Google DeepMind, in which the AI-focused research unit introduces a new weather projection model trained on decades of historical weather data across hundreds of variables.

The team claimed this method, called GraphCast, outperforms existing prediction systems across more than 90% of 1,380 measures and can better account for the types of extreme weather events that are growing more common amid the climate crisis.

The findings come as weather data is becoming a priority for businesses trying to gird their operations for increasingly erratic climate patterns. DeepMind is far from the first team to attempt to apply AI and historical data to the problem. But the researchers claim GraphCast sets a new benchmark for accuracy and speed of calculation, the latter of which reduces the resources needed to produce a computation.

“It’s definitely an inflection point in weather forecasting,” Rémi Lam, staff research scientist at DeepMind and a lead author on the paper, said in a press call. “It shows the extent to which machine learning and AI can really deal in and really process extremely complex physical phenomena.”

Keep reading here.—PK

A tech tool from the University of Chicago aims to prevent AI from being like your friend in high school and totally stealing your look.

Artists can submit their work to a platform called Glaze, which applies small changes to a digital image—tiny modifications to pixel color here, little artifacts added there—and gets the model trained on a different version of a design that someone wants to protect from theft.

A lead developer on the Glaze team thinks of the artwork changes like UV light—something a human can’t see, but AI can.

“The models, they have mathematical functions looking at images very, very differently from just how the human eye looks,” Shawn Shan, a grad researcher at the University of Chicago who demoed the tool for IT Brew, said.

An invite-only web version of the mechanism allows someone to send images from phones, tablets, or any device with a browser. You just have to upload your work, provide an intensity of the change, and hit “Run.” WebGlaze emails you the result and then deletes all images, according to its site.

“The goal is to protect art style from being copied from artwork itself. These models are powerful. They can learn a style from just five to 10 images,” Shan told IT Brew.

Keep reading here.—BH