It was a eureka moment for Jibran Ilyas. Like much of his party, the Pakistan Tehreek-e-Insaf (PTI), Ilyas had been swamped by a sense of uncertainty. Their charismatic leader, former Prime Minister Imran Khan, has been in jail for months. Senior party officials are in hiding. Campaigning in any meaningful way for the February 8 elections to the National Assembly and provincial legislatures appeared difficult, if not near-impossible.

It's been an eventful weekend at OpenAI's headquarters in San Francisco. In a surprise move Friday, the company's board of directors fired co-founder and CEO Sam Altman, which set off an institutional crisis that has seen senior staff resign in protest with nearly 700 rank-and-file employees threatening to do the same. Now the board is facing calls for its own resignation, even after Microsoft had already swooped in to hire Altman's cohort away for its own AI projects. Here's everything you need to know about the situation to hold your own at Thanksgiving on Thursday. This saga began forever ago by internet standards, or last Thursday in the common parlance.

Over the last decade, deep learning systems have shown an astonishing ability to classify images, translate languages, and perform other tasks that once seemed uniquely human. However, these systems work opaquely and sometimes make elementary mistakes, and this fragility could be intentionally exploited to threaten security or safety. In 2018, for example, a group of undergraduates at the Massachusetts Institute of Technology (MIT) three-dimensionally (3D) printed a toy turtle that Google's Cloud Vision system consistently classified as a rifle, even when viewed from various directions. Other researchers have tweaked an ordinary-sounding speech segment to direct a smart speaker to a malicious website. These misclassifications sound amusing, but they could also represent a serious vulnerability as machine learning is widely deployed in medical, legal, and financial systems.

Machine learning algorithms, which use large amounts of data to power everything from your email to language translation, are being heralded as the next big thing in technology. The only problem is, they're vulnerable. Over the last few years, researchers have shown how one type of machine learning algorithm called an image classifier–think of it as a program to which you can show a picture of your pet, and it will tell you if it's a dog or cat–are weak in a surprising way. These programs are susceptible to attacks from something called "adversarial examples." An adversarial example occurs when you show the algorithm what is clearly an image of a dog, but instead of seeing a dog, a glitch that human eyes can't detect make the classifier see a picture of guacamole instead.

Dr Ilya Romanenko played a key role in R&D leadership for 12 years at image sensor designer Apical and after the company was acquired by ARM in 2016 he became R&D Director for ARM's computer vision team. He wants to combine Spectral Edge's proven Phusion image processing technology with a new approach based on Deep Learning for a new range of imaging technology for smartphones. "Spectral Edge is built on impressive fundamental technology, which sits at the intersection of the image processing and computer vision fields, meaning I can use my knowledge and expertise in both to move the company forward," said Romanenko. "It is already delivering significant benefits to companies in the broadcast market, and I am confident that working with the team we can bring this technology to life, particularly within products in the mobile sector, improving the user experience and bringing a new quality to existing products." His appointment follows that of new CEO Rhodri Thomas, who joined from SwiftKey/Microsoft in February 2017.

Artificial Intelligence is a fascinating topic for many people nowadays, no matter if they are a consumer or an influencer. Today, I'm happy to be joined by Ilya Gelfenbeyn, CEO and co-founder of Api.ai, a conversational UX platform used to embed natural language understanding capabilities into connected devices, apps and services. Regular readers of SitePoint may recognize the service, as we have covered Api.ai in the past with a series earlier this year on getting started with the platform. Ilya has a background in machine learning, natural language processing and conversational interfaces. Elio: We have covered Api.ai in the past, but could you briefly explain the concept behind it?