machine learning



Accelerating the Power of AI with Neural Networks - AI Trends

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Supervised neural networks are algorithms that can differentiate and make judgements based on image or pattern recognition, after being trained with labeled data.


Researchers use biological evolution to inspire machine learning

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As Charles Darwin wrote in at the end of his seminal 1859 book On the Origin of the Species, "whilst this planet has gone cycling on according to the fixed law of gravity, from so simple a beginning endless forms most beautiful and most wonderful have been, and are being, evolved." Scientists have since long believed that the diversity and range of forms of life on Earth provide evidence that biological evolution spontaneously innovates in an open-ended way, constantly inventing new things. However, attempts to construct artificial simulations of evolutionary systems tend to run into limits in the complexity and novelty which they can produce. This is sometimes referred to as "the problem of open-endedness." Because of this difficulty, to date, scientists can't easily make artificial systems capable of exhibiting the richness and diversity of biological systems.


Why Is Law So Slow To Use Data?

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"Data is the oil of the digital era," proclaims a 2017 Economist article. Big business--especially tech giants like Alphabet (Google's parent), Amazon, Facebook, and Apple among others-- are mining data like Standard Oil processed petroleum a century before. Why is the legal industry still running on gut and instinct while the businesses it serves are propelled by data? A recent survey by business analytics powerhouse RELX Group polled 1,000 U.S. senior executives across the health care, insurance, legal, science, banking industries as well as government. Law finished last among industries--just ahead of government--in utilizing big data in some form.


Ocrolus raises $24 million to scan financial documents with computer vision

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Ocrolus, a New York startup that taps AI and machine learning to parse financial documents, today announced it has raised $24 million in a series B round led by venture growth equity firm Oak HC/FT. Ocrolus cofounder and CEO Sam Bobley said the fresh capital, which follows a $4 million series A in April 2018 and brings the company's total raised to about $30 million, will fuel expansion into verticals like consumer and auto lending and advance development of the company's underwriting solutions for banks. "Sometimes humans are better than robots," said Bobley, who added that Ocrolus has quintupled in size since April 2018 and now counts hundreds of financial services companies among its customer base. "We combine machine processes with live human intelligence to provide customers with a complete solution. The capital will be used to develop workflows for new document types and sharpen our fraud detection and analytical capabilities."


Ocrolus raises $24 million to scan financial documents with computer vision

#artificialintelligence

Ocrolus, a New York startup that taps AI and machine learning to parse financial documents, today announced it has raised $24 million in a series B round led by venture growth equity firm Oak HC/FT. Ocrolus cofounder and CEO Sam Bobley said the fresh capital, which follows a $4 million series A in April 2018 and brings the company's total raised to about $30 million, will fuel expansion into verticals like consumer and auto lending and advance development of the company's underwriting solutions for banks. "Sometimes humans are better than robots," said Bobley, who added that Ocrolus has quintupled in size since April 2018 and now counts hundreds of financial services companies among its customer base. "We combine machine processes with live human intelligence to provide customers with a complete solution. The capital will be used to develop workflows for new document types and sharpen our fraud detection and analytical capabilities."


Watson Studio Desktop is now free for academia - IBM Watson - Medium

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Machine Learning, Data Science, and Predictive Analytics techniques are in strong demand. That's why since its launch, IBM Watson Studio has proven to be very popular with academia. Thousands of students and faculty have been drawn to Watson Studio for its powerful open source and code-free data analysis tools. Now, this all-in-one platform for data science is free to students and faculty with unlimited use with Watson Studio Desktop. Watson Studio Desktop, with unlimited compute, is now available for free to students and faculty for teaching and learning purposes via a 1 year subscription.


MIT AI tool can predict breast cancer up to 5 years early, works equally well for white and black patients – TechCrunch

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MIT's Computer Science and Artificial Intelligence Lab has developed a new deep learning-based AI prediction model that can anticipate the development of breast cancer up to five years in advance. Researchers working on the product also recognized that other similar projects have often had inherent bias because they were based overwhelmingly on white patient populations, and specifically designed their own model so that it is informed by "more equitable" data that ensures it's "equally accurate for white and black women." That's key, MIT notes in a blog post, because black women are more than 42 percent more likely than white women to die from breast cancer, and one contributing factor could be that they aren't as well-served by current early detection techniques. MIT says that its work in developing this technique was aimed specifically at making the assessment of health risks of this nature more accurate for minorities, who are often not well represented in development of deep learning models. The issue of algorithmic bias is a focus of a lot of industry research and even newer products forthcoming from technology companies working on deploying AI in the field.


AI simulates the universe fast and accurately--and its creators don't know how it does it Amazing Science

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"We can run these simulations in a few milliseconds, while other'fast' simulations take a couple of minutes," says study co-author Shirley Ho, a group leader at the Flatiron Institute's Center for Computational Astrophysics in New York City and an adjunct professor at Carnegie Mellon University. The speed and accuracy of the project, called the Deep Density Displacement Model, or D3M for short, wasn't the biggest surprise to the researchers. The real shock was that D3M could accurately simulate how the universe would look if certain parameters were tweaked--such as how much of the cosmos is dark matter--even though the model had never received any training data where those parameters varied. "It's like teaching image recognition software with lots of pictures of cats and dogs, but then it's able to recognize elephants," Ho explains. "Nobody knows how it does this, and it's a great mystery to be solved."


Episode 30: Keeping Eyes Healthy and Saving Vision…with Artificial Intelligence - Dell Technologies

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Eyes are more than the "windows to the soul." As such, ocular health and neurological health are intertwined. The most skilled ophthalmologists can read ocular scans to not only look for eye disease, but also traces of a host of neurological disorders. Voxeleron is using artificial intelligence and machine learning to, as they put it, "democratize expertise." Their algorithms hold the promise of delivering expert-level diagnostic capabilities to any lab with a scanning device.