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.

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.

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.

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.

I am a Post-Doctoral Associate in the Computer Science Department at Courant Institute of Mathematical Sciences, New York University. I am working in the Laboratory of prof. Since January 2017 I will be an Assistant Professor in the Department of Electrical and Computer Engineering at NYU Tandon School of Engineering. I received my PhD from the Department of Electical Engineering at Columbia University in the City of New York, where I was also the Fu Foundation School of Engineering and Applied Science Presidential Fellowship holder (in years 2009-2012). I was co-advised by prof.

We've been naughty at Basecamp. Since before the launch of version 3, almost a year ago, we've had an internal API for chatbots. This allowed us to pipe in GitHub commits and control our operations infrastructure from Campfire. It was a quick, hackish version, but it was enough to make it work -- well, work for us. Finally it's time to atone and bring chatbots to everyone!

Today a new nonprofit organization called the Partnership on Artificial Intelligence to Benefit People and Society announced its establishment. Participants include Amazon, Google (and Google's DeepMind) Facebook, IBM, and Microsoft. Those companies will put up money and research resources (that could mean talent, open-source code, or data). Company representatives will sit on the organization's board alongside people from academia, the nonprofit world, and policy and ethics experts, according to a statement. Plans call for discussions, studies, reports, best practices, and public outreach in general.