These days, a lot of workers are worried about robots taking their jobs, but now robots are taking jobs that literally no one else was doing--like poring through every inch of people's dense expense reports. AppZen, a startup that provides automated auditing services, has just expanded its software, which can now not only read basic items on attached receipts, but also scan entire documents to look for clues about invalid charges. Anant Kale, the company's CEO, tells Fast Company that the new offering, called ReceiptIQ, can audit 100% of the expense reports that employees submit, spotting them for "accidental fraud . . . The upgrade required moving beyond optical character recognition to computer vision that can understand the entire receipt, such as recognizing company logos. Many hotels put their logos on receipts rather than spelling out their name, says Kale. ReceiptIQ analysis goes deeper by looking for context, such as whether car rental bills include a fuel service charge--a penalty for not returning the car with a full gas tank.

The world's largest technology companies hold the keys to some of the largest databases on our planet. Much like goods and coins before it, data is becoming an important currency for the modern world. The data's value is rooted in its applications to artificial intelligence. Whichever company owns the data, effectively owns AI. Right now that means companies like Facebook, Amazon, Alphabet, IBM and Microsoft have a ton of power.

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Any conversation about the current state of tech would be incomplete without mention of Machine Learning--tech companies like Uber, Microsoft, Google, and more are doubling down on the latest wave of programming that's making once futuristic inventions like artificial intelligence, self-driving cars, and smart homes a reality. Believe it or not, you can learn the fundamentals of Machine Learning even those with little to no programming background. Right now, you can save hundreds on the Complete Machine Learning Bundle, featuring 10 in-depth courses and over 60 hours of hands-on training to get you up to speed on the latest machine learning skills. Normally over 700, Engadget readers can get the full bundle for just 39.99 at GDGT Deals. Throughout this comprehensive training bundle, you'll learn fundamental machine learning concepts like decision trees, deep learning, and NLP (neuro-linguistic programming), get hands on training in Python, Java, and other essential coding languages, and apply your skills building recommendation systems and solving big data problems.

Artificial intelligence is one of those tech terms that seems to inevitably conjure up images (and jokes) of computer overlords running sci-fi dystopias -- or, more recently, robots taking over human jobs. But AI is already here: It's powering your voice-activated digital personal assistants and Web searches, guiding automated features on your car and translating foreign texts, detecting your friends in photos you post on social media and filtering your spam. But as practical uses of AI have exploded in recent years, one critical element remains missing: an industrywide set of ethics standards or best practices to guide the growing field. Now, the industry heavyweights are partnering to fill that gap. Called the Partnership on Artificial Intelligence to Benefit People and Society, the group consists of Amazon, Facebook, Google, Microsoft and IBM. Apple is also in talks to join.

Just a few weeks ago, we posted about some incredible research from Vijay Kumar's lab at the University of Pennsylvania getting quadrotors to zip through narrow gaps using only onboard localization. This is a big deal, because it means that drones are getting closer to being able to aggressively avoid obstacles without depending on external localization systems. The one little asterisk to this research was that the quadrotors were provided the location and orientation of the gap in advance, rather than having to figure it out for themselves. Yesterday, Davide Falanga, Elias Mueggler, Matthias Faessler, and Professor Davide Scaramuzza, who leads the Robotics and Perception Group at the University of Zurich, shared some research that they've just submitted to ICRA 2017. It's the same kind of aggressive quadrotor maneuvering, except absolutely everything is done on board, including obstacle perception.

Every day, we talk to artificial intelligence practitioners who are either labeling data internally for training AI models, or they're using crowdsourcing (or outsourcing) for the labeling/annotating. Both are bummers; that's why we exist. Recently, we covered the issues with an in-house approach. If you need only simplistic training data--say, categorized images or ranked articles--then maybe a crowdsourcing solution will cut it. But if you need more sophisticated data, you need good tooling--stuff to do bounding boxes, polygons, segmentation masks, pixel-level annotation, semantic segmentation, and so on.

Google, Facebook, Amazon, IBM and Microsoft are joining forces to create a new AI partnership dedicated to advancing public understanding of the sector, as well as coming up with standards for future researchers to abide by. Going by the unwieldy name of the Partnership on Artificial Intelligence to Benefit People and Society, the alliance isn't a lobbying organisation (at least, it says it "does not intend" to lobby government bodies). Instead, it says it will "conduct research, recommend best practices, and publish research under an open license in areas such as ethics, fairness and inclusivity; transparency, privacy, and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability and robustness of the technology". There will be equal representation between corporate and non-corporate members on the board of the partnership, and it hopes to invite "academics, non-profits and specialists in policy and ethics" to join. Each of the five founding corporate members has strong AI research teams, some of which have become household names, such as IBM's Watson and Amazon's Alexa.

When it comes to policing artificial intelligence, technology leaders think there is safety in numbers. A new organization called the Partnership on Artificial Intelligence to Benefit People and Society will seek to foster public dialogue and create guidelines for developing AI so that systems do not misbehave. The companies involved include Google and its subsidiary DeepMind, Facebook, Amazon, Microsoft, and IBM. The partnership is founded on eight tenets or principles, including the idea that AI should benefit as many people as possible; that the public should be involved in its development; that research should be conducted in an open way; and that AI systems should be able to explain their reasoning. That such fierce rivals would come together in this way shows how important the companies feel it is to head off public concern and speculation over the potential impacts of AI.

The regular engagement of experts across multiple disciplines (including but not limited to psychology, philosophy, economics, finance, sociology, public policy, and law) to discuss and provide guidance on emerging issues related to the impact of AI on society.