In the foothills of the Sierra Mountains, a few hours east of San Francisco, are the Moaning Caverns, a cave system that begins, after a narrow, twisting descent of 30-some feet, with an abrupt 180-foot drop. The Park Service has found ancient human skeletons at the bottom of the drop. Instead, these explorers took one step too far in the gloom. The skeletons belonged to adolescents. After all, adolescence is the time of life when someone is most likely to join a cult, kill, be killed, invent an art form, help overthrow a dictator, ethnically cleanse a village, care for the needy, transform physics, adopt a hideous fashion style, commit to God, and be convinced that all the forces of history have converged to make this moment the most consequential ever, fraught with peril and promise. For all this we can thank the teenage brain. Some have argued adolescence is a cultural construct. In traditional cultures, there is typically a single qualitative transition to puberty. After that, the individual is a young adult. Yet the progression from birth to adulthood is not smoothly linear.

You wake up on a bus, surrounded by all your remaining possessions. A few fellow passengers slump on pale blue seats around you, their heads resting against the windows. You turn and see a father holding his son. But one man, with a salt-and-pepper beard and khaki vest, stands near the back of the bus, staring at you. You feel uneasy and glance at the driver, wondering if he would help you if you needed it. When you turn back around, the bearded man has moved toward you and is now just a few feet away.

Creating driverless cars capable of humanlike reasoning is a long-standing pursuit of companies like Waymo, GM's Cruise, Uber, and others. Intel's Mobileye proposes a mathematical model -- the Responsibility-Sensitive Safety (RSS) -- it describes as a "common sense" approach to on-the-road decision-making that codifies good habits like giving other cars the right of way. For its part, Nvidia is actively developing Safety Force Field, a decision-making policy in a motion-planning stack that monitors unsafe actions by analyzing real-time sensor data. Now, a team of MIT scientists are investigating an approach that leverages GPS-like maps and visual data to enable autonomous cars to learn human steering patterns, and to apply the learned knowledge to complex planned routes in previously unseen environments. Their work -- which will be presented at the International Conference on Robotics and Automation in Long Beach, California next month -- builds on end-to-end navigation systems architected by Daniel Rus, director of the Computer Science and Artificial Intelligence Laboratory (CSAIL).

The global analysis of Artificial Intelligence In Finance Market and its upcoming prospects have recently added by Research N Reports to its extensive repository. It has been employed through the primary and secondary research methodologies. This market is expected to become competitive in the upcoming years due to the new entry of a number of startups in the market. Additionally, it offers effective approaches for building business plans strategically which helps to promote control over the businesses. "Artificial Intelligence is the intelligence which is shown by machines. Cognitive computing, Chatbots, Personal Assistant, Machine Learning are all peripherals of AI used in the finance industry extensively nowadays."

Jason Yang, an IMES research scientist, is the lead author of the paper, which appears in the May 9 issue of Cell. Other authors include Sarah Wright, a recent MIT MEng recipient; Meagan Hamblin, a former Broad Institute research technician; Miguel Alcantar, an MIT graduate student; Allison Lopatkin, an IMES postdoc; Douglas McCloskey and Lars Schrubbers of the Novo Nordisk Foundation Center for Biosustainability; Sangeeta Satish and Amir Nili, both recent graduates of Boston University; Bernhard Palsson, a professor of bioengineering at the University of California at San Diego; and Graham Walker, an MIT professor of biology.

The UK has been knocked from the top spot of a global ranking of countries whose governments are ready to capitalise on artificial intelligence technologies in public services. The UK was narrowly beaten to the number one position by Singapore in this year's Government AI Readiness Index, which the ranking's authors described as a "timely reminder of the ongoing inequality of access to AI". This is the second time the ranking has been produced, with the UK having topped the leaderboard in the first iteration in 2017. Technology consultancy Oxford Insights and the Canadian government-sponsored International Development Research Centre said the 2019 Government AI Readiness Index should prompt governments to "act to ensure that global inequalities are not further entrenched or exacerbated by AI". Unsurprisingly, the upper echelons of the ranking were dominated by higher-income countries with strong economies.

When we program morality into robots, are we doomed to disappoint them with our very human ethical inconsistency? In his newest novel, Machines Like Me, the British writer Ian McEwan takes on the rise of artificial intelligence, exploring how humans would react to the creation of perfectly human-like robots. But he does it in his particularly McEwan-esque fashion. Rather than creating a work of speculative fiction set in a near future where general artificial intelligence has become a reality, McEwan sets Machines Like Me in an alternate past, a 1980s London where the internet already exists and the English A.I. pioneer Alan Turing -- who in our world was effectively hounded to death by government authorities in 1954 because of his homosexuality -- instead lived and went on to create the first true A.I.: a collection of androids for purchase called Adams and Eves. Why paranoia about digital voice assistants is overblown.

New Tech Affiliate Partners CognitiveScale, Kore.ai and Shibumi Highlight Power and Innovation Behind Blue Prism's connected-RPA Offering ORLANDO, FLA – May 23, 2019 -- Continuing to push the envelope for innovation around intelligent automation capabilities, Blue Prism (AIM: PRSM) today announced that CognitiveScale, Kore.ai and Shibumi have joined the company's Technology Alliance Program (TAP) as affiliates. These new partners will help drive digital transformations for their clients by extending Blue Prism's connected-RPA capabilities to include AI-powered chatbots along with workflow and data synchronization solutions being delivered in a Software-as-a-Service (SaaS) model. "Each month Blue Prism adds a few key technology partners that show us the art of the possible with our digital workforce," says Linda Dotts, SVP Global Partner Strategy and Programs for Blue Prism. "Our connected-RPA platform provides a bedrock foundation for enterprise customers looking to drive innovation through new intelligent automation capabilities. This latest group of technology partner affiliates highlights the depth and breadth of our rapidly evolving ecosystem."

For all of the hype about artificial intelligence (AI), most software is still geared toward engineers. To demystify AI and unlock its benefits, the MIT Quest for Intelligence created the Quest Bridge to bring new intelligence tools and ideas into classrooms, labs, and homes. This spring, more than a dozen Undergraduate Research Opportunities Program (UROP) students joined the project in its mission to make AI accessible to all. Undergraduates worked on applications designed to teach kids about AI, improve access to AI programs and infrastructure, and harness AI to improve literacy and mental health. Six projects are highlighted here.

AI is not a silver bullet, but the technology can positively impact different sectors in a number of ways. Most organisations, as a result, are fully invested in AI, but they are hampered by a lack of AI skills. In fact, more than half don't have the required in house skilled talent to execute their strategy, according to new research from SnapLogic. The study found that 93% of US and UK organisations consider AI to be a business priority and have projects planned or already in production. However, more than half of them (51%) acknowledge that they don't have the right mix of AI skills in-house to bring their strategies to life.