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Machine learning in cell biology – teaching computers to recognize phenotypes

#artificialintelligence

Commercially available motorized microscopes can yield data at a throughput of 105 images per day, raising a strong need for automated data analysis (Conrad and Gerlich, 2010; Lock and Strömblad, 2010). Computational data analysis not only reduces the workload for the experimentalist, but also ensures objectivity and consistency in the annotation of large data sets (Danuser, 2011). The complexity and diversity in microscopic image data, however, poses challenges for developing suitable data analysis workflows. Bioimage informatics methods offer powerful solutions for specific image analysis tasks, such as object detection, motion analysis or measurements of morphometric features (Danuser, 2011; Murphy, 2011; Eliceiri et al., 2012; Myers, 2012). Most image analysis algorithms, however, have been developed for specific biological assays.


Georgia Tech's AI Teaching Assistant Fools (Some) Humans (EdSurge News)

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Imagine if your teaching assistant was actually a robot--and looked like Alicia Vikander. A picture of the "Ex Machina" lead actress graces a Wall Street Journal article that explores students' surprise when they discovered one of their teaching assistants was, in fact, a bot. Her responses--which fooled even former IBM employees--were based on looking through nearly 40,000 questions and answers on a discussion forum. Ashok Goel, the professor who teaches the online Georgia Tech computer science course, believes that bots like Jill can answer 40 percent of all students' questions--many of the mundane variety--within a year. Best quote of the story goes to a student: "We're taking an artificial intelligence class. There should be some artificial intelligence here."


Chip Maker Movidius Unveils AI On A Stick: What Can Fathom Do?

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Movidius has announced the Fathom Neural Compute Stick, which is claimed to be the first acceleration module for deep learning in the world, alongside the Fathom deep learning software framework. The Fathom Neural Compute Stick utilizes Movidius' ultra-low power, high performance processor, the Myriad 2, allowing the device to operate neutral networks using power below 1 watt. The device not only looks like a USB stick, but it also functions as one, connecting to a USB port across a wide range of devices. In combination with the Fathom deep learning software framework, the Fathom Neural Compute Stick will allow neural networks to be taken down from the cloud and then deployed directly into end-user devices. Embedded in the Fathom Neural Compute Stick is Google's machine learning software named TensorFlow, which is primarily used for vision processing.


Imagine Discovering That Your Teaching Assistant Really Is a Robot

#artificialintelligence

One day in January, Eric Wilson dashed off a message to the teaching assistants for an online course at the Georgia Institute of Technology. "I really feel like I missed the mark in giving the correct amount of feedback," he wrote, pleading to revise an assignment. Thirteen minutes later, the TA responded. "Unfortunately, there is not a way to edit submitted feedback," wrote Jill Watson, one of nine assistants for the 300-plus students. Last week, Mr. Wilson found out he had been seeking guidance from a computer.


A law firm has hired an AI "lawyer" to cut through the drudgery of corporate law

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The first job after law school can be horrendous--not simply because of the intense workload and long hours, but also the drudgery. A huge amount of legal work given to those on the lowest rung of the ladder consists of reading through hundreds of pages of notes, articles, and case precedents, to provide senior lawyers with legal details that can help build their case. Fortunately, artificial intelligence is up to the task. So much so that century-old law firm BakerHostetler has formally hired its first "digital attorney," ROSS, as an artificially intelligent legal researcher. ROSS is working with BakerHostetler's bankruptcy team as part of a partnership first announced last month, at Vanderbilt Law School's "Watson, Esq." conference on law and artificial intelligence.


In-depth Machine Learning Course w/ Python • /r/MachineLearning

@machinelearnbot

Hi there, my name is Harrison and I frequently do Python programming tutorials on PythonProgramming.net and YouTube.com/sentdex. I do my best to produce tutorials for beginner-intermediate programmers, mainly by making sure nothing is left to abstraction and hand waving. The most recent series is an in-depth machine learning course, aimed at breaking down the complex ML concepts that are typically just "done for you" in a hand-wavy fashion with packages and modules. The machine learning series is aimed at just about anyone with a basic understanding of Python programming and the willingness to learn. If you're confused about something we're doing, I can either help, or point you towards a tutorial that I've done already (I have about 1,000) to help.


AI Teaching Assistant Helped Students Online--and No One Knew the Difference

#artificialintelligence

Meet Jill Watson, a first-time teaching assistant at Georgia Tech assigned to moderate an online forum for a computer science class. Jill was 1 of 9 TAs assigned to help answer questions about coursework and projects from the 300 students enrolled in the advanced course. During the first few weeks in January, Jill really struggled. This was Knowledge-Based Artificial Intelligence, after all, a course with the goal to "build AI agents capable of human-level intelligence and gain insights into human cognition." It was also a requirement for graduate students to earn their master's degree.


Greg Durrett

@machinelearnbot

I am a sixth-year graduate student in Computer Science at UC Berkeley, advised by Dan Klein. I work on a range of topics in statistical natural language processing, including coreference resolution, entity linking, and syntactic parsing. My work combines two broad thrusts: first, designing joint models that combine information across different tasks (TACL 2014) or across different views of a problem (ACL 2015), and second, building systems that strike a balance between being linguistically motivated and data driven (EMNLP 2013, ACL 2014). When I'm not doing NLP, I like to play the clarinet. I currently play in the UC Berkeley Symphony Orchestra.


Amazon open-sources its own deep learning software, DSSTNE

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Amazon has suddenly made a remarkable entrance into the world of open-source software for deep learning. Yesterday the ecommerce company quietly released a library called DSSTNE on GitHub under an open-source Apache license. Deep learning involves training artificial neural networks on lots of data and then getting them to make inferences about new data. Several technology companies are doing it -- heck, it even got some air time recently in the show "Silicon Valley." And there are already several other deep learning frameworks to choose from, including Google's TensorFlow.


Schools should teach digital technology, says former Education Secretary

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Schools need to place more focus on teaching young people digital skills, according to former Education Secretary Lord Kenneth Baker. Baker, who is Chairman of education charity the Edge Foundation, warned that millions of jobs are under threat from automation and that jobs in professions that were once considered careers for life are being lost. According to Baker, many professional jobs are under threat from artificial intelligence, and it could have an impact on sectors such as the law, transport and construction. He has produced the Digital Revolution report urging the education system to tackle the way in which technological changes will affect the jobs market. The report provides an in-depth look at the digital revolution and how it will affect employment and education. Baker stated that more emphasis should be placed on digital skills, which he said are "almost entirely absent from the core curriculum in mainstream schools."