Thursday, February 11, 2016

Machine Learning News Issue 8

Welcome to the Momenta Learning News on Machine Learning. This is issue 8, please feel free to share this post.

Active machine learning-driven experimentation to determine compound effects on protein patterns

High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments.

Microsoft won't miss out on the next big tech trend

Microsoft is determined not to miss out on artificial intelligence (AI), the next big trend in technology that will, over time, filter into how everyone uses hardware, software, and the internet. Unlike mobile, which the company missed ( and continues to miss) by a mile, Microsoft has been working hard to get on top of AI, both in terms of research and integrating it into products.

The Tiny Startup Racing Google to Build a Quantum Computing Chip

Rigetti Computing is working on designs for quantum-powered chips to perform previously impossible feats that advance chemistry and machine learning. The airy Berkeley office space of startup Rigetti Computing boasts three refrigerators-but only one of them stores food. The other two use liquid helium to cool experimental computer chips to a fraction of a degree from absolute zero.

Wolves Have Different 'Howling Dialects,' Machine Learning Finds

Researchers have used algorithms to distinguish different wolf dialects. Image: Arik Kershenbaum Differentiating wolf howls with human ears can prove tricky, so researchers have turned to computer algorithms to suss out if different wolf species howl differently.

Reverse-engineering the brain to improve machine learning -- GCN

Researchers are working to reverse-engineer how the brain's visual system processes information in hopes of advancing machine learning algorithms and computer vision. The Machine Intelligence from Cortical Networks (MICrONS) research program seeks to unlock the brain's learning methods in an effort to make computers process information more like humans do.

​Why machine learning may help stop payment fraud

In 2017, the New Payments Platform (NPP) - infrastructure that offers real time payments between financial institutions and their customers' accounts - will come into effect. This essentially means that payments will be visible in a customer's account within around 10 seconds.

Will Machines Really Replace Insurance Agents?

There has been a lot of talk lately about "machine learning," and how it enables computer systems to evolve algorithms, without programmer intervention, as these systems take in updated knowledge and insights. In other words, algorithms are capable of learning and making appropriate shifts in the predictions they produce.

ESI Group: Acquisition of Mineset Inc., a Big Data Visual Analytics and Machine-Learning Specialist

PARIS--()--Regulatory News: ESI Group (Paris:ESI): Alain de Rouvray, ESI Group's Chairman and CEO, comments: "This acquisition complements the recent integration of Picviz Labs (now 'INENDI') and its technology for big data mining. Combining INENDI's data correlation detection with Mineset's pattern recognition, and linking both to ESI Group's Virtual Prototyping solutions, provides a new transformative process and source of value creation, particularly in the traditional Virtual Engineering domain.

Companies Are Reimagining Business Processes with Algorithms

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April HPC User Forum to Tackle Deep Learning, HPC in the Cloud, and More

IDC released the preliminary agenda for this spring's HPC User Forum, held April 11-13 in Tucson, AZ. Deep Learning, HPC in the Cloud, and NSCI are among the themes being tackled. There's also a technology update from Intel and a look at HPC in Europe on the agenda.

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