After a Falcon 9 rocket stage burned up in the atmosphere, vaporised lithium and other metals drifted over Europe. A SpaceX rocket that burned up after re-entering the atmosphere unleashed a plume of vaporised metals over Europe, a type of pollution that is expected to increase as spacecraft and satellites multiply. The upper stage of a Falcon 9, which is designed to splash down in the Pacific Ocean for possible re-use, lost control due to engine failure and fell from orbit over the north Atlantic in February 2025. We're finally solving the puzzle of how clouds will affect our climate People across Europe saw fiery debris streaking through the sky, some of which crashed behind a warehouse in Poland. Seeing the news, Robin Wing at the Leibniz Institute of Atmospheric Physics in Germany and his colleagues turned on their lidar, an instrument for atmospheric sensing.

Toddlers may swiftly master the meaning of the word "no", but many artificial intelligence models struggle to do so. They show a high fail rate when it comes to understanding commands that contain negation words such as "no" and "not". That could mean medical AI models failing to realise that there is a big difference between an X-ray image labelled as showing "signs of pneumonia" and one labelled as showing "no signs of pneumonia" – with potentially catastrophic consequences if physicians rely on AI…

I remember having written a response that was specifically focused on Andrew Ng's Deep Learning training that was launched with a lot of fanfare in October last year. I have added excepts from my Quora answer here and there and this is me just visiting my own answers based on my year long experience since June 2017 working with CEOs and Chair(wo)men of large enterprises, training about 9000 people in my classical (meaning hands-on workshops where we learn the old fashioned way face-to-face) and interacting with tens of thousands of learners worldwide. I will however be brutally honest about my initial observation of the first 1.5 weeks -- which I went through yesterday with great anticipation and truly enjoyed (still enjoying!), of what I experienced. This may actually not have anything to do with his capabilities or intentions rather it("the dilemma") owes this to latest trend (pretty much close to madness) of packing a deep learning course in a MOOC and try to teach to folks everything in bunch of nutshells. I'll get to that in a minute, but first my quick analysis of who this Deep Learning course / specialization may or may not be for. So, who might this course be for?

Or it's possibly the most disturbing thing you've seen. A computer, sounding like a human with'umms' and pauses a normal conversation would feature, getting a human to book an appointment. Apart from an army of personal assistants and executive assistants reaching to high-five Google, this move throws up some important issues for businesses. Let's play devil's advocate for a second, this robot can fool a human. Do the different parties have a right to know what is happening?

Machines don't actually have bias. AI doesn't'want' something to be true or false for reasons that can't be explained through logic. Unfortunately human bias exists in machine learning from the creation of an algorithm to the interpretation of data – and until now hardly anyone has tried to solve this huge problem. A team of scientists from Czech Republic and Germany recently conducted research to determine the effect human cognitive bias has on interpreting the output used to create machine learning rules. The team's white paper explains how 20 different cognitive biases could potentially alter the development of machine learning rules and proposes methods for "debiasing" them. Biases such as "confirmation bias" (when a person accepts a result because it confirms a previous belief) or "availability bias" (placing greater emphasis on information relevant to the individual than equally valuable information of less familiarity) can render the interpretation of machine learning data pointless.

Give us your feedback Thank you for your feedback. Artificial intelligence is one of the important technological advances of the early 21st century. Already it has meant that machines can read medical images as well as a radiologist, and enabled the auto industry to develop autonomous cars. The technology is in danger of being overrated, however, and considerably more work is needed before we can reach the long-dreamt-of moment when machine intelligence matches the human variety. When we discuss AI today we are mainly referring to just one facet of it: deep learning.

Give us your feedback Thank you for your feedback. Artificial intelligence is one of the important technological advances of the early 21st century. Already it has meant that machines can read medical images as well as a radiologist, and enabled the auto industry to develop autonomous cars. The technology is in danger of being overrated, however, and considerably more work is needed before we can reach the long-dreamt-of moment when machine intelligence matches the human variety. When we discuss AI today we are mainly referring to just one facet of it: deep learning.

As artificial intelligence is increasingly considered the wave of the future, some leading business executives are starting to worry that the technology won't stop at regulating your thermostat or telling you how to get to work. Will the next round of advances mean Siri can do your job? Business heads ranging from Tesla's (TSLA) Elon Musk to Alibaba's (BABA) Jack Ma certainly think so. Meanwhile, billionaire and Dallas Mavericks owner Mark Cuban seems freaked out about AI. "However much change you saw over the past ten years with the Apple (AAPL) iPhone, that's nothing," Cuban said at a recent conference. Cuban also claims that Montreal and China are "kicking our ass" with artificial intelligence. Cuban also expressed concern about technology usurping the current standard of everyday business practices, leaving many unemployed.

For years now, some of the best, wildest, most moving or revealing stories we've been telling ourselves have come not from books, movies or TV, but from video games. So we're running an occasional series, Reading The Game, in which we take a look at some of these games from a literary perspective. They march and they argue. They taunt their human slaves and, when they pass close enough, I can hear them talking about me -- Talion, called Gravewalker, murdered Captain of Gondor brought back to life by magic and the influence of my mostly-invisible elf/wraith buddy, Celebrimbor, who is a ghost that lives in my head. I am bored out of my elf-inhabited mind.

Astro Teller has an unusual way of starting a new project: He tries to kill it. Teller is the head of X, formerly Google X, the advanced technology lab of Alphabet. At X's headquarters not far from the Googleplex in Mountain View, Calif., Teller leads a group of engineers, inventors, and designers devoted to futuristic "moonshot" projects like self-driving cars, delivery drones, and Internet-beaming balloons. To turn their wild ideas into reality, Teller and his team have developed a unique approach. It starts with trying to prove that whatever it is that you're trying to do can't be done--in other words, trying to kill your own idea. As Teller explains, "Instead of saying, 'What's most fun to do about this or what's easiest to do first?' we say, 'What is the most likely reason this project won't make it?' The ideas that survive get additional rounds of scrutiny, and only a tiny fraction eventually becomes official projects; the proposals that are found to have an Achilles' heel are ...