Carol Reiley, president and cofounder of autonomous car tech startup Drive.ai, "How do you create a robot that people can trust? That's what we're working on," says co-founder and president Carol Reiley, 34, a Johns Hopkins University PhD candidate who paused her studies to move west and wrangle her Stanford-trained peers into startup mode. This tidy formula of study hall, garage start-up, technological disruption, is well known and beloved in Silicon Valley. Larry Page and Sergey Brin started Google in a garage near their Palo Alto, Calif.

Hewlett Packard Enterprise has made no secret of its desire to push further into big data, and on Tuesday it announced two key new offerings: HPE Haven OnDemand Combinations, an extension of the "machine learning as a service" platform it released earlier this year, and Vertica 8, a major new update to its analytics software. Launched in March, HPE's Haven OnDemand cloud platform offers machine learning APIs (application programming interfaces) and services designed to help developers and businesses build data-rich applications. The platform now has 70 artificial intelligence APIs and more than 18,000 users, and HPE is extending it to make development easier. Haven OnDemand Combinations, a cloud service built on top of OnDemand, provides a catalogue of pre-built and customizable machine learning APIs and a drag-and-drop interface for mixing and matching them. Developers can string together APIs and copy and paste the code directly into their development projects, HPE said.

However, the real risk posed by AI – at least in the near term – is much more insidious. The Center for Human-Compatible Artificial Intelligence, launched this week with 5.5m in funding from the Open Philanthropy Project, is lead by computer science professor and artificial intelligence pioneer Stuart Russell. "The potential benefits [of AI research] are huge, since everything that civilization has to offer is a product of human intelligence; we cannot predict what we might achieve when this intelligence is magnified by the tools AI may provide, but the eradication of disease and poverty are not unfathomable," the letter reads. Similarly, an artificially intelligent hedge fund designed to maximize the value of its portfolio could be incentivized to short consumer stocks, buy long on defence stocks and then start a war – as suggested by Elon Musk in Werner Herzog's latest documentary.

MUMBAI: Gurgaon-based startup Staqu Technologies has entered into a research partnership with Indraprastha Institute of Information Technology, Delhi to boost research in the field of artificial intelligence and deep learning. "This partnership will be the first of its kind in India as we aim to develop cutting edge deep learning based algorithms to tackle problems currently plaguing consumers worldwide," said Atul Rai, co-founder & CEO of Staqu Technologies in a statement. Experts from both the organizations will be working on creating innovative solutions in the domains of video and image understanding. IIIT Delhi is one of the leading institutes in the field of Artificial Intelligence and computer vision, with Infosys granting it a large amount to advance research and technology. Dr. Chetan Arora of the CSE Department from IIIT Delhi will be the Principal Investigator on this collaboration.

Hewlett Packard Enterprise has made no secret of its desire to push further into big data, and on Tuesday it announced two key new offerings: HPE Haven OnDemand Combinations, an extension of the "machine learning as a service" platform it released earlier this year, and Vertica 8, a major new update to its analytics software. Launched in March, HPE's Haven OnDemand cloud platform offers machine learning APIs (application programming interfaces) and services designed to help developers and businesses build data-rich applications. The platform now has 70 artificial intelligence APIs and more than 18,000 users, and HPE is extending it to make development easier. Haven OnDemand Combinations, a cloud service built on top of OnDemand, provides a catalog of pre-built and customizable machine learning APIs and a drag-and-drop interface for mixing and matching them. Developers can string together APIs and copy and paste the code directly into their development projects, HPE said.

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PALO ALTO, CA--(Marketwired - Aug 30, 2016) - Hewlett Packard Enterprise (NYSE: HPE) today announced the availability of HPE Haven OnDemand (HoD) Combinations, a new cloud-based offering built on the HPE Haven OnDemand platform that enables developers to apply the power of machine learning to build next generation applications. The new offering provides a pre-built catalogue of cognitive services and an intuitive drag and drop interface. Developers can chain together multiple machine learning APIs into combinations and copy and paste the code directly into their development projects, to quickly and easily create breakthrough mobile and enterprise applications. "HPE HoD Combinations represents the next step in our vision to democratize machine learning for mainstream developers and help them build the next generation of cognitive applications," said Fernando Lucini (@fernandolucini), Chief Technology Officer, Big Data Platform, HPE Software. "Through HPE HoD Combinations, enterprise developers now have access to the building blocks required to take their application development to the next level through an easy and intuitive solution."

Go from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized dataset with this quick reference for the busy data scientist. Understand text mining, machine learning, and network analysis; process numeric data with the NumPy and Pandas modules; describe and analyze data using statistical and network-theoretical methods; and see actual examples of data analysis at work. This one-stop solution covers the essential data science you need in Python. Data science is one of the fastest-growing disciplines in terms of academic research, student enrollment, and employment. Python, with its flexibility and scalability, is quickly overtaking the R language for data-scientific projects.

No one in Luke Scott's "Morgan" acts like a human, which is fine enough for some of his characters -- after all, this is a film about a genetically engineered being run totally amok -- but becomes slightly more problematic once the film attempts to dig deeply into themes relating to human emotion, human behavior, human fallibility…the list goes on and on. "Morgan," for all its ambitious sci-fi trappings, is really a film about how being human is hard and messy and weird, a message that's difficult to deliver by way of wooden lines, worse delivery and a series of cheap, gotcha! "twists" that do its audience no favors. Lee Weathers (Kate Mara) is something of a fixer -- a "risk management consultant" for a shady corporation who seems to only be dispatched when things have already gone way past risky (mention is made throughout the film of some sort of incident that happened in Helsinski, one of the few genuinely tantalizing tidbits to make its way into the final film). Her latest job seems to be just the kind she likes: a hard one that hinges on her staying stone-faced, opaque and exceedingly rigid.

The study involved a self-learning artificial intelligence system, GloVe. It has the ability to read and interpret online text. "We replicate these using a widely used, purely statistical machine-learning model--namely, the GloVe word embedding--trained on a corpus of text from the Web," reads the study. But when researchers offered GloVe a list of white and black-sounding names, the robot went absolutely racist! The intelligent system identified names that are common among white people as "pleasant", while African-American names were categorized as "unpleasant" words. "Our results indicate that language itself contains recoverable and accurate imprints of our historic biases," the researchers told RNS.