AI, RPA, and machine learning, you must have heard these words echoing in the tech industry. Be it blogs, websites, videos, or even product descriptions, disruptive technologies have made their presence bold. The fact that we all have AI-powered devices in our homes is a sign that the technology has come so far. If you are under the impression that AI, robotic process automation, and machine learning have nothing in common, then here's what you need to know, they are all related concepts. Oftentimes, people use these names interchangeably and incorrectly which causes confusion among businesses that are looking for the latest technological solutions.

Developing responsible artificial intelligence is about more than just good engineering, said Alka Patel, chief of responsible AI with the U.S. Department of Defense's Joint Artificial Intelligence Center (JAIC). Responsible AI requires well-trained professionals working with the data processing, she said, which requires bridging the gap in AI literacy. The Department of Defense has a strong safety culture, Ms. Patel said, and that is critical to the JAIC's approach to AI policies and processes. At the beginning of the pandemic, for example, there were major concerns around grocery store supply chains, so the JAIC developed a prototype AI tool to better predict when certain zip codes may begin panic-buying. This tool also helps better inform the U.S. military's response to crises.

The US Army's new'Enhanced Night Vision' technology makes fighting in darkness look like a video game for soldiers. The Lancer Brigade, a US military combat unit, posted video of the high-tech equipment, which shows people and objects outlined in a glowing white light, to its Twitter account last month. The Enhance Night Vision Goggle-Binoculars replaces the traditional green night vision experience to help soldiers see more effectively in low light. The Army says its new device uses white phosphor tubes instead of the traditional green phosphor, which it says offers troops better contrast to see enemies, equipment and weapons. The new goggles include a set of binoculars and an augmented reality system and soldiers will also be able to use them to look through the scope of a weapon remotely.

And it starts right at the beginning. Instead of the Hmong word for "hello" or "welcome," she says, is "something else that said, like, 'your honor' or'the queen' or'the king' instead." Seeing something so simple done incorrectly was frustrating and off-putting. "Not only was it just probably churned through Google Translate, it wasn't even peer edited and reviewed to ensure that there was fluency and coherence," she says. Xiong says this kind of carelessness is common online--and it's one reason she and others in the Hmong community can feel excluded from politics.

The field of artificial intelligence is detonating with products like IBM Watson, DeepMind's AlphaZero, and voice recognition used in virtual assistants including Amazon's Alexa, Apple's Siri, and Google's Home Assistant. Due to the massive impact of AI on humans' lives, the concern is growing about how to adopt a sound ethical AI strategy to shape future developments. Building ethical AI requires both an ethical way for building AI systems and a strategy for making AI systems themselves moral. For instance, engineers of self-driving vehicles should consider their social results including guaranteeing that the vehicles are fit for making moral decisions. Subsequently, building ethical use of artificial intelligence that we can trust should be at the core of its plan and development. The process of building ethical AI, in any case, is definitely not straightforward.

Last week, I taught a cybersecurity course at the University of Oxford case. I felt that this is significant because typically the problem domain of AI and cybersecurity is mostly an Anomaly detection or a Signature detection problem. Also, most of the times, cybersecurity professionals use specific tools such as splunk or darktrace(which we cover in our course) – but these threats and their mitigations are very new. Hence, they need exploring from first principles/research. Thus, we can cover newer threats such as adversarial attacks(making modifications to input data to force machine-learning algorithms to behave in ways they're not supposed to).

We're three and a half years away from electing another president here in the US, but it's never to early too prepare ourselves for the impending crapshow that is US politics. The good news is, going forward, you won't have to think so much. The age of data-based politics is coming to a close thanks to the innovations created by the 2016 Donald Trump campaign and the counteracting tactics employed by the Biden team in 2020. Data used to be the most important commodity in politics. When Trump won in 2016, it wasn't on the strength of his platform (he didn't have one).

Hopefully you notice a shorter commute, but you might not notice why. "If you are looking closely, you can probably see the fisheye camera, but other than that it'll look like all the other intersections," said Pima County Department of Transportation's Assistant Division Manager of Maintenance and Operations Michelle Montagnino. The new system will use cameras, sensors and artificial intelligence to better estimate traffic volumes, arrivals on red and side-street delays. But she says privacy issues are not a concern. "Maybe you can make out a make and a color, definitely not a model, you're not going to tell license plate information, driver, or any of that information," she said.

Deep neural networks excel at finding patterns in datasets too vast for the human brain to pick apart. That ability has made deep learning indispensable to just about anyone who deals with data. This year, the MIT Quest for Intelligence and the MIT-IBM Watson AI Lab sponsored 17 undergraduates to work with faculty on yearlong research projects through MIT's Advanced Undergraduate Research Opportunities Program (SuperUROP). Students got to explore AI applications in climate science, finance, cybersecurity, and natural language processing, among other fields. And faculty got to work with students from outside their departments, an experience they describe in glowing terms.

House Republicans are moving closer to ousting Conference Chair Liz Cheney (R-Wyo.) What we're hearing: Most members recognize Cheney can't be succeeded by a white man, given their top two leaders -- House Minority Leader Kevin McCarthy (R-Calif.)