But once Feldman was hired to write the personality of a chatbot for Kasisto, a startup that focuses on artificial intelligence software for banks, she became vocal about the importance of taking gender out of the identity equation. Under her watch, MyKai, the bot she was hired to craft a personality for, would be neither female nor male. Feldman's boss at Kasisto, Dror Oren, says the work the team has done with the bot made him more outspoken about the need for equality in tech than he'd have imagined going into the project, and he's a self-proclaimed feminist to begin with. Now, he's hyperaware of the differences between the personality of Kai and overly feminine answers inside similar products made by most large tech companies. Kasisto is on to something.

Apple has acknowledged for the first time that it is investing in building a self-driving car. In a letter to US transport regulators, Apple said it was "excited about the potential of automated systems in many areas, including transportation". It added that there were "significant societal benefits of automated vehicles" to be realised. There have long been rumours about the firm's plans but it has not publicly admitted them. However, Ford, which itself plans to have self-driving cars on the road by 2021, has said it was working on the basis that Apple was building one. The tech firm has already registered several car-related internet domains, including apple.car and apple.auto.

When Skechers started building a colossal distribution center in Moreno Valley six years ago, backers promised a wave of new jobs. Instead, by the time the company moved to the Moreno Valley, it had closed five facilities in Ontario that employed 1,200 people and cut its workforce by more than half. Today, spotting a human on the premises can feel like an accomplishment. There are now only about 550 people working at one cavernous warehouse, which is about as big as two Staples Centers combined. Many of them sit behind computer screens, monitoring the activities of the facility's true workhorses: robotic machines.

We have self-driving cars, knowledgeable digital assistants, and software capable of putting names to faces as well as any expert. Google recently announced that it had developed software capable of learning--entirely without human help--how to play several classic Atari computer games with skill far beyond that of even the most callus-thumbed human player. But do these displays of machine aptitude represent genuine intelligence? For decades artificial-intelligence experts have struggled to find a practical way to answer the question. AI is an idea so commonplace that few of us bother to interrogate its meaning.

Ford announced it will plans to start testing its autonomous vehicles on European roads by next year as it ramps up its robot car strategy. According to Digital Trends the U.S. car manufacturing goliath is moving ahead with European testing as it pursues its ambitious strategy to introduce fully autonomous vehicles for ride-hailing by 2021. "It is important that we extend our testing to Europe," said Ford of Europe's manager for Automated Driving Thomas Lukaszewicz. "Rules of the road vary from country to country here, traffic signs and road layouts are different, and drivers are likely to share congested roads with cyclists." Testing will begin at Ford's Engineering Center in Essex, U.K. After this, trials will be expanded to its Germany-based Research & Advanced Engineering facilities in Cologne and Aachen.

EVERY day more than 8,000 containers flow through the Port of Rotterdam. But only a fraction are selected to pass through a giant x-ray machine to check for illicit contents. The machine, made by Rapiscan, an American firm, can capture images as the containers move along a track at 15kph (9.3mph). But it takes time for a human to inspect each scan for anything suspicious--and in particular for small metallic objects that might be weapons. To increase this inspection rate would require a small army of people.

TechCrunch Disrupt in London is on December 5-6. As well as speakers and panels, we'll be featuring some demos by some amazing tech companies. The first will be by Boston Dynamics. Yes, folks, delegates to Disrupt London will get to see one of those amazing BD robots up close and personal, almost literally in the flesh (if they had any flesh, that is). Marc Raibert, CTO and founder of Boston Dynamics will be demonstrating one of the amazing robots his team has created, but you'll have to come to find out which one… Raibert was a professor of electrical engineering and computer science at MIT and a member of the Artificial Intelligence Laboratory from 1986 through 1995.

As the fourth industrial revolution, characterised by smart factories and digital manufacturing, makes its presence felt globally, there is an upsurge in handwringing about the notion that technology will eliminate human jobs. Labour's deputy leader Tom Watson has even launched a new commission to study the future of work and tackle fears about the rise of the machines. Yet these concerns aren't new; they go back to the first Industrial Revolution some 250 years ago and the Canut revolts in France, as well as the Luddite resistance in Britain. "Nowadays, people who worry about new technologies are often dismissed as living in the past. That would not be fair; such concerns must be addressed seriously," Christine Lagarde, head of the International Monetary Fund, said at a conference recently.

When Robert Schapire started studying theoretical machine learning in graduate school three decades ago, the field was so obscure that what is today a major international conference was just a tiny workshop, so small that even graduate students were routinely excluded. But it has become one of the hottest fields in computer science, turning once-obscure academic gatherings like the upcoming Annual Conference on Neural Information Processing Systems in Barcelona, Spain, into a sold-out affair attended by thousands of computer scientists from top corporations and academic institutions. "It's been really something to see this field develop, and to see things that seemed impossible become possible in my lifetime," said Schapire, a principal researcher in Microsoft's New York City research lab whose machine learning research is widely used in the field. The NIPS conference, which starts Monday, is so popular because machine learning has quickly become an indispensable tool for developing technology that consumers and businesses want, need and love. Machine learning is the basis for technology that can translate speech in real time, help doctors read radiology scans and even recognize emotions on people's faces.

However, there are two distinct species both referred to as "bots": The first article of this series argued that the latter have a number of serious disadvantages that make them virtually unacceptable. They face problems with deep linking, discoverability and lack of bot-to-bot communication protocols. Intelligent conversational agents offer an intriguing solution to these problems: they don't need new protocols or APIs to communicate with each other and with "master bots" such as Google Assistant. They will communicate in plain English! Bots are the new websites -- every organization will soon have its own bot.