Symantec has launched Endpoint Protection 14, a new security solution which harnesses artificial intelligence to protect clients. Announced on November 1, the new security offering is powered by AI and machine learning on the endpoint and in the cloud. Symantec says that by harnessing machine learning to collate data and detect patterns and anomalies which may indicate a cyberattack, AI provides "a multi-layered solution able to stop advanced threats and respond at the endpoint regardless of how the attack is launched." Symantec Endpoint Protection combines machine learning, memory exploit mitigation, and threat intelligence provided by Symantec and Blue Coat, which combined their research and security operations in October after Symantec completed the acquisition of Blue Coat for $4.6 billion. The company also says that the solution is capable of 99.9 percent efficacy, low false positives, and a 70 percent carbon footprint reduction in comparison to past endpoint software.

IBM Research have created an open-source artificial intelligence robot called TJ Bot. Downloading the source via GitHub – coders can 3D print or Laser Cut the template, attach a Raspberry Pi and integrate it with IBM Watson API's. These include Watson Tone Analyzer, Watson Speech to Text API and Watson Conversation. TJ Bot is an example of'embodied cognition' – the idea of embedding artificial intelligence into objects in our everyday lives.

Borland theorises that, just as has been the case with waves of automation since the industrial revolution, technology is creating jobs as fast as it is eradicating them. New digital technologies have increased demand for software designers, programmers and managers, while lower costs of production from automation have resulted in higher real incomes that in turn lead to more demand and more jobs. But there is one difference. This time, big data and advances in computerisation mean technology is no longer replacing low-skilled blue collar jobs.

Deep Learning can be described as a new machine learning toolkit that has a high likelihood to lead to more advanced forms of artificial intelligence. The evidence for this is in the sheer number of breakthroughs that had occurred since the beginning of this decade. There is a new found optimism in the air and we are now again in a new AI spring. Unfortunately, the current state of deep learning appears to many ways to be akin to alchemy. Everybody seems to have their own black-magic methods of designing architectures.

SAP acquired procurement software vendor Ariba in 2011, but the company's history dates back two decades. This week, SAP Ariba executives briefed analysts in Boston, giving an overview of recent roadmap milestones as well as a look ahead at what's yet to come. Growth markers: There are now 2.4 million suppliers on Ariba's business network, with more than $1 trillion in commerce transactions each year. In addition, Ariba has a presence in 190 countries. Yet Ariba has set some lofty goals for additional growth.

Earlier this year, Andreessen Horowitz investor Chris Dixon noted the challenge investors face in helping to groom promising AI startups, given how quickly Facebook, Google, and Amazon are bringing aboard related talent. Dixon noted, for example, that Wit.ai, a Y Combinator startup that built voice-activated interfaces that Facebook bought and which now powers its Messenger platform, was only in Andreessen Horowitz's portfolio for a few months when Facebook bought it. But firm co-founder Marc Andreessen said on stage at Disrupt today that the firm is beginning to see things swing in the opposite direction. "Two years ago, it seemed like four or five companies were hoovering up all the talent . . . I think something like 1,500 people over four years [were involved in] building Alexa," the technology that powers Amazon's voice-controlled home computer Echo.

All-natural and organic are familiar terms to consumers, and anything artificial has become anathema to many. Unless we're talking artificial intelligence – or AI – then investors should be hungry to learn as much as possible about a technology that is becoming as ubiquitous as organic tofu. The vast majority of nearly 2,000 experts polled by the Pew Research Center in 2014 said they anticipate robotics and artificial intelligence will permeate wide segments of daily life by 2025. A 2015 study covering 17 countries found that artificial intelligence and related technologies added an estimated 0.4 percentage point on average to those countries' annual GDP growth between 1993 and 2007, accounting for just over one-tenth of those countries' overall GDP growth during that time. Interesting numbers – but just what is artificial intelligence?

Ben Dickson is a software engineer and the founder of TechTalks. As artificial intelligence and machine learning mature and manifest their potential to take on complicated tasks, we've become somewhat expectant that robots can succeed where humans have failed -- namely, in putting aside personal biases when making decisions. But as recent cases have shown, like all disruptive technologies, machine learning introduces its own set of unexpected challenges and sometimes yields results that are wrong, unsavory, offensive and not aligned with the moral and ethical standards of human society. While some of these stories might sound amusing, they do lead us to ponder the implications of a future where robots and artificial intelligence take on more critical responsibilities and will have to be held responsible for the possibly wrong decisions they make. At its core, machine learning uses algorithms to parse data, extract patterns, learn and make predictions and decisions based on the gleaned insights.

Mark Zuckerberg and his wife, Priscilla Chan, have laid out plans to invest $3bn over the next 10 years with the not insignificant goal of tackling all diseases. "Can we cure, prevent or manage all disease by the end of this century?" The Chan Zuckerberg Initiative will focus on some of the world's biggest killers, including heart disease, cancer, infectious diseases and neurological diseases. One of its biggest investments is to be a $600m "Biohub" at UCSF, which will bring together scientists and engineers from Stanford, Berkeley and UCSF – who haven't collaborated in this way before – to develop tools to treat diseases. The second focus will be transformative technology, all of which will be made available to all scientists everywhere. "Throughout the history of science, most of the major scientific breakthroughs have been preceded by some new tool and technology that allows you to see in new ways," explained Zuckerberg.

Anthony Foxx waits for the countdown, then hits the plunger. The catapult releases its bungee cord, slinging the drone from to a standstill to 50 mph in half a second. The drone spins up its twin propellers and flies a few hundred feet up, circling overhead. "That's amazing," Foxx says, as the UAV drops its package within a few feet of the practice delivery zone, then belly flops onto a brown landing pad that resembles the base of a jumping castle. During the closing months of his four-year run as US Secretary of Transportation, Foxx has come to California on a fact finding mission.