So you know the Bayes rule. How does it relate to machine learning? It can be quite difficult to grasp how the puzzle pieces fit together - we know it took us a while. This article is an introduction we wish we had back then. While we have some grasp on the matter, we're not experts, so the following might contain inaccuracies or even outright errors.

What keeps software developers up at night, other than coding? The fear that artificial intelligence systems can replace them, according to a new survey. Evans Data Corp., in a survey of 550 software developers, asked them about the most worrisome thing in their careers. A plurality, 29%, chose this answer: "I and my development efforts are replaced by artificial intelligence." Surprisingly, this concern about A.I. topped the second-most identified worry, which was that the platform the developer is working on will become obsolete (23%), or doesn't catch on (14%). Concerns about A.I. replacing software developers has academic support.

The number of sophisticated cognitive technologies that might be capable of cutting into the need for human labor is expanding rapidly. But linking these offerings to an organization's business needs requires a deep understanding of their capabilities. If popular culture is an accurate gauge of what's on the public's mind, it seems everyone has suddenly awakened to the threat of smart machines. Several recent films have featured robots with scary abilities to outthink and manipulate humans. In the economics literature, too, there has been a surge of concern about the potential for soaring unemployment as software becomes increasingly capable of decision making. Yet managers we talk to don't expect to see machines displacing knowledge workers anytime soon -- they expect computing technology to augment rather than replace the work of humans.

At one of the busiest shipping terminals in the U.S., more than two dozen giant red robots wheeled cargo containers along the docks on a recent morning, handing the boxes off to another set of androids gliding along long rows of stacked containers before smoothly setting the boxes down in precise spots. The tightly designed dance at TraPac LLC's Los Angeles terminal offers a window on how global trade will move in the near future: using highly automated systems and machinery, with minimal human intervention, to handle the flood of goods that new free-trade agreements will push to the docks. Many in the industry believe automation, which boosts terminal productivity and reliability while cutting labor costs, is critical to the ability of ports to cope with the surging trade volumes and the huge megaships that are beginning to arrive in the U.S. Analysts estimate the technology can reduce the amount of time ships spend in port and improve productivity by as much as 30%. "We have to do it for productivity purposes, to stay relevant and to be able to service these large ships," said Peter Stone, a member of TraPac's board. Yet the TraPac site is one of only four cargo terminals in the U.S. using the technology.

A long-lost portrait of a historic computer – built in 1951 and now the oldest working digital computer in the world – has resurfaced on a cafe bar wall in Manchester. The artist John Yeadon first saw the Witch (the Wolverhampton Instrument for Teaching Computation from Harwell) in 1982 in the Museum of Science and Industry in Birmingham. He was fascinated, even though it had become a sad ghost of its former glory at the cutting edge of computing technology. He tried to capture its character – which he described as a "diabolical contraption, a dusty hunk of electric and mechanical hardware that reminded me of the disturbing 1950's Quatermass science fiction television series" – in a near-lifesize two metre by three metre Portrait of a Dead Witch, which he also intended as a joke about the contemporary craze for computer-generated art. He described it as a portrait rather than a still life: "I think I had some idea that the painting brought the computer back to life, or at least to another life."

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Tasked by their CEOs to use technology to better align the business with shifting customer preferences, CIOs across every industry are leveraging the now-standard social, mobile, analytics and cloud (SMAC) technologies to modernize, stabilize and accelerate digital transformations. But those tools will get some company from augmented and virtual reality, the Internet of Things, blockchain software and advanced analytics over the next 18 to 24 months. These emerging technologies are fueling new products and services, changing the way businesses operate and interact with customers, Bill Briggs, CTO of Deloitte Consulting, told CIO.com. "Every company is a technology company at its core," says Briggs, who wrote the report, whose theme is "Innovating in a Digital Era." "Technology is the most strategic asset. Briggs says the real value of IoT, in which sensors attached to everyday machines send data to other machines, is that it enables companies to reimagine business processes by automating previously manual.

Christoffer O. Hernæs is vice president of Strategy, Innovation and Analysis at Sparebank 1 Group, Norway's second-largest financial institution. Artificial intelligence is one of the hottest subjects these days, and recent advances in technology make AI even closer to reality than most of us can imagine. The subject really got traction when Stephen Hawking, Elon Musk and more than 1,000 AI and robotics researchers signed an open letter issuing a warning regarding the use of AI in weapons development last year. The following month, BAE Systems unveiled Taranis, the most advanced autonomous UAV ever created; there are currently 40 countries working on the deployment of AI in weapons development. Those in the defense industry are not the only ones engaging in an arms race to create advanced AI. Tech giants Facebook, Google, Microsoft and IBM are all engaging in various AI-initiatives, as well as competing on developing digital personal assistants like Facebook's M, Cortana from Microsoft and Apple' Siri.

It's hard enough for non-technical users to deal with ransomware infections: understanding public-key cryptography, connecting to the Tor anonymity network and paying with Bitcoin cryptocurrency. A new malicious program now makes it even more difficult by completely locking victims out of their computers. The new Petya ransomware overwrites the master boot record (MBR) of the affected PCs, leaving their operating systems in an unbootable state, researchers from antivirus firm Trend Micro said in a blog post. The MBR is the code stored in the first sectors of a hard disk drive. It contains information about the disk's partitions and launches the operating system's boot loader.

This article is a part of an evolving theme. Here, I explain the basics of Deep Learning and how Deep learning algorithms could apply to IoT and Smart city domains. Specifically, as I discuss below, I am interested in complementing Deep learning algorithms using IoT datasets. I elaborate these ideas in the Data Science for Internet of Things program which enables you to work towards being a Data Scientist for the Internet of Things (modelled on the course I teach at Oxford University and UPM – Madrid). Deep learning is often thought of as a set of algorithms that'mimics the brain'. A more accurate description would be an algorithm that'learns in layers'.