We take a look at categories where AI startups are beginning to emerge. A majority of them are in the early stages of funding. We take a look at categories where AI startups are beginning to emerge. A majority of them are in the early stages of funding. Artificial Intelligence is being hailed as the new linchpin of the tech industry.

There is little doubt that Artificial Intelligence (AI) will transform industries and business models. Recent developments in driverless cars, voice recognition, and deep learning show how much machines can do and the powerful business models AI can drive. Driven both by opportunity and a fear of losing out, companies across industries have announced AI-focused initiatives. However, early AI pilots are not producing the dramatic results that technology enthusiasts predicted and executives expected. The opportunity for augmenting jobs with AI is way larger than replacement of humans.

Participants run ahead of Puerto de San Lorenzo's fighting bulls during the third bull run of the San Fermin festival in Pamplona, northern Spain. Each day at 8:00 am hundreds of people race with six bulls, charging along a winding, 848.6-metre (more than half a mile) course through narrow streets to the city's bull ring, where the animals are killed in a bullfight or corrida, during this festival, immortalised in Ernest Hemingway's 1926 novel "The Sun Also Rises" and dating back to medieval times and also featuring religious processions, folk dancing, concerts and round-the-clock drinking. Iraqi women, who fled the fighting between government forces and Islamic State (IS) group jihadists in the Old City of Mosul, cry as they stand in the city's western industrial district awaiting to be relocated

There have been many kinds of books, with many kinds of meanings. This one book was special because it was the first fictional story produced via artificial intelligence. It was the first book in the sense that its contents made sense. Before this book, all other attempts of letting an AI write a book had produced things that were pastiches of randomness. A couples of sentences here and there surrounded by text that made no sense.

Samsung's Bixby voice assistant for the Galaxy S8 and galaxy S8 Plus is finally available worldwide. Bixby Voice is now being rolled out to more than 200 countries. Unfortunately, the service will only work in English and Korean languages for now. "Now millions of customers worldwide have access to a new and intelligent way of interacting with their phone," executive VP and head of R&D for Samsung's Mobile Business Injong Rhee said. "The expansion of Bixby's voice capabilities is an initial step in the continued rollout of Bixby functionality. In the future, Bixby will have the learning power to offer more intelligent and personalized interactions and seamless connections across more devices."

After months of delays, Samsung has finally launched its Bixby voice assistant in more than 200 countries worldwide. Among the countries with access to the smart assistant are the UK, Australia, Canada and South Africa – although it can only understand American English and Korean. The launch will come as a huge relief to Samsung, which suffered major delays as Bixby'struggled to understand English.' It operates through'Quick Commands' – a feature that allows users to create custom voice commands. For example, users can use the command'good night' as a shortcut for'Turn on Do-not-disturb mode, set an alarm for 6:00am and turn on blue light filter.'

Samsung has faced a tough slog getting Bixby to the masses, but now its voice assistant is accessible in more than 200 countries including the UK, Australia, Canada and South Africa. It's been available in South Korea and the US since July, when it launched after months of delays. Part of Bixby's appeal is its positioning beyond that of a simple voice assistant. Samsung claims it learns over time, recognizing "natural language" to make interacting with your phone easier and more intuitive. It understands cross-application commands and thanks to deep integration it can be accessed without any interruptions to what you're already doing on-screen.

Machine learning is perhaps the principal technology behind two emerging domains: data science and artificial intelligence. The rise of machine learning is coming about through the availability of data and computation, but machine learning methdologies are fundamentally dependent on models. The emergence of machine learning is closely tied to the emergence of widely available data. Large amounts of data and high interconnection bandwidth mean that we receive much of our information about the world around us through computers. Economists try to measure productivity, one of the ways we can become more productive is by becoming more efficient. For example, moving from gathering food to settled agriculture. In the modern era one approach to becoming more efficient is automation of processes like manufacturing production lines. The manufacturing process is decomposed into a series of mechanical or manual processes each of which is applied sequentially. Manufacturing processes consist of production lines and robotic automation. Logistics can also be decomposed into the supply chain processes. Whether it's manufacturing or logistics, efficiency can be improved by automating components of the processes to improve the flow of goods. An interesting challenge for modern society is the management of both the flow of goods and the flow of information. The flow of information is also highly automated. Processing of data is decomposed into stages in computer code. In these processing pipelines, manufacturing, logistics or data management, the overall pipeline normally also requires human intervention from an operator. These interventions can create bottlenecks and slow the process of automation. Machine learning is the key technology in automating these manual stages. The human interventions that were easy to replicate with technology have already been replaced. The components that still require human intervention are the knottier problems. Often they represent components that are difficult, or impossible, to decompose into stages which could then be further automated. In that sense these components are process-atoms. In manufacturing or logistics settings these atoms involve the sort of flexible manual skills that we cannot replicate with current robotic technology.

Image recognition AIs that have been trained by some of the most-used research-photo collections are developing sexist biases, according to a new study. University of Virginia computer science professor Vicente Ordóñez and colleagues tested two of the largest collections of photos and data used to train these types of AIs (including one supported by Facebook and Microsoft) and discovered that sexism was rampant. He began the research after noticing a disturbing pattern of sexism in the guesses made by the image recognition software he was building. 'It would see a picture of a kitchen and more often than not associate it with women, not men,' Ordóñez told Wired, adding it also linked women with images of shopping, washing, and even kitchen objects like forks. The AI was also associating men with stereotypically masculine activities like sports, hunting, and coaching, as well as objects sch as sporting equipment.

SUBIRATS, SPAIN – Spanish police on Monday shot dead an Islamist militant who killed 13 people with a van in Barcelona last week, ending a five-day manhunt for the perpetrator of Spain's deadliest attack in over a decade. Police said they tracked 22-year-old Younes Abouyaaqoub to a rural area near Barcelona and shot him after he held up what looked like an explosives belt and shouted "Allahu Akbar" (God is Greatest). A bomb squad then used a robot to approach his body. Abouyaaqoub had been on the run since Thursday evening, after he drove at high speed into throngs of strollers along Barcelona's most famous avenue, Las Ramblas. After fleeing the scene, he hijacked a car and fatally stabbed its driver.