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Can six billion cells phones collecting data on how people move lead to better human health?

Can six billion cells phones collecting data on how people move lead to better human health? | Social Foraging | Scoop.it

Collecting and analyzing information from simple cell phones can provide surprising insights into how people move about and behave—and even help us understand the spread of diseases.

 

At a computer in her office at the Harvard School of Public Health in Boston, epidemiologist Caroline Buckee points to a dot on a map of Kenya’s western highlands, representing one of the nation’s thousands of cell-phone towers. In the fight against malaria, Buckee explains, the data transmitted from this tower near the town of Kericho has been epidemiological gold.

 

When she and her colleagues studied the data, she found that people making calls or sending text messages originating at the Kericho tower were making 16 times more trips away from the area than the regional average. What’s more, they were three times more likely to visit a region northeast of Lake Victoria that records from the health ministry identified as a malaria hot spot. The tower’s signal radius thus covered a significant waypoint for transmission of malaria, which can jump from human to human via mosquitoes. Satellite images revealed the likely culprit: a busy tea plantation that was probably full of migrant workers. The implication was clear, Buckee says. “There will be a ton of infected [people] there.”

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Dynamics of Social Interaction
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Fast-Spiking Interneurons Supply Feedforward Control of Bursting, Calcium, and Plasticity for Efficient Learning

Fast-spiking interneurons (FSIs) are a prominent class of forebrain GABAergic cells implicated in two seemingly independent network functions: gain control and network plasticity. Little is known, however, about how these roles interact. Here, we use a combination of cell-type-specific ablation, optogenetics, electrophysiology, imaging, and behavior to describe a unified mechanism by which striatal FSIs control burst firing, calcium influx, and synaptic plasticity in neighboring medium spiny projection neurons (MSNs). In vivo silencing of FSIs increased bursting, calcium transients, and AMPA/NMDA ratios in MSNs. In a motor sequence task, FSI silencing increased the frequency of calcium transients but reduced the specificity with which transients aligned to individual task events. Consistent with this, ablation of FSIs disrupted the acquisition of striatum-dependent egocentric learning strategies. Together, our data support a model in which feedforward inhibition from FSIs temporally restricts MSN bursting and calcium-dependent synaptic plasticity to facilitate striatum-dependent sequence learning.

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Combining Convolutional Neural Networks and LSTMs for Segmentation-Free OCR

We present a novel end-to-end trainable OCR system combining a CNN for feature extraction with 1-D LSTMs for sequence modeling. We present results on English and Arabic handwriting data, and on English machine print data, showing state-of-the-art performance. We believe that our method is simpler than existing 2D LSTM models, and will make it easier to use techniques borrowed from CNN research in computer vision to improve OCR performance.
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What is the Team Data Science Process?

What is the Team Data Science Process? | Social Foraging | Scoop.it
The Team Data Science Process (TDSP) is an agile, iterative data science methodology to deliver predictive analytics solutions and intelligent applications efficiently. TDSP helps improve team collaboration and learning. It contains a distillation of the best practices and structures from Microsoft and others in the industry that facilitate the successful implementation of data science initiatives. The goal is to help companies fully realize the benefits of their analytics program.

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Diffix: High-Utility Database Anonymization

Diffix: High-Utility Database Anonymization | Social Foraging | Scoop.it
In spite of the tremendous privacy and liability benefits of anonymization, most shared data today is only pseudonymized. The reason is simple: there haven’t been any anonymization technologies that are general purpose, easy to use, and preserve data quality. This paper presents the design of Diffix, a new approach to database anonymization that promises to break new ground in the utility/privacy trade-off. Diffix acts as an SQL proxy between the analyst and an unmodified live database. Diffix adds a minimal amount of noise to answers—Gaussian with a standard deviation of only two for counting queries—and places no limit on the number of queries an analyst may make. Diffix works with any type of data and configuration is simple and data-independent: the administrator does not need to consider the identifiability or sensitivity of the data itself. This paper presents a high-level but complete description of Diffix. It motivates the design through examples of attacks and defenses, and provides some evidence for how Diffix can provide strong anonymity with such low noise levels.

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Differential privacy at the end of the rainbow

Differential privacy at the end of the rainbow | Social Foraging | Scoop.it
Apple’s heavily-marketed but proprietary implementation of differential privacy is no longer secret. Researchers at the University of Southern California
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Quants Bring AI and Blockchain Together in One Fund

Quants Bring AI and Blockchain Together in One Fund | Social Foraging | Scoop.it
A group of quantitative hedge fund traders long dreamed of bringing their artificial intelligence strategies to all. And now they have with the first exchange-traded fund to combine the worlds of AI and blockchain.
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IBM partnership aims to create smart shipping port with IoT sensors, AI, big data

IBM partnership aims to create smart shipping port with IoT sensors, AI, big data | Social Foraging | Scoop.it
IBM and the Port of Rotterdam are partnering to create a digitized smart shipping port, complete with IoT sensors and other connected devices.
By becoming a smart shipping port, the Port of Rotterdam will use data to boost efficiency and drive down cost.
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Predicting Future Lane Changes of Other Highway Vehicles using RNN-based Deep Models

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As the Powerful Argue AI Ethics, Might Superintelligence Arise on the Fringes?

As the Powerful Argue AI Ethics, Might Superintelligence Arise on the Fringes? | Social Foraging | Scoop.it
Last year, Elon Musk and Stephen Hawking admitted they were concerned about artificial intelligence. While undeniably brilliant, neither are AI researchers. Then this week Bill Gates leapt into the fray, also voicing concern—even as a chief of research at Microsoft said advanced AI doesn’t worry him. It’s a hot topic. And hotly debated. Why? In part, it’s because tech …
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Is There a Trade-off Between Immediate and Longer-term AI Safety Efforts? - Future of Life Institute

Is There a Trade-off Between Immediate and Longer-term AI Safety Efforts? - Future of Life Institute | Social Foraging | Scoop.it
Is There a Trade-off Between Immediate and Longer-term AI Safety Efforts?
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Pixie: A System for Recommending 3+ Billion Items to 200+ Million Users in Real-Time

User experience in modern content discovery applications critically depends on high-quality personalized recommendations. However, building systems that provide such recommendations presents a major challenge due to a massive pool of items, a large number of users, and requirements for recommendations to be responsive to user actions and generated on demand in real-time. Here we present Pixie, a scalable graph-based real-time recommender system that we developed and deployed at Pinterest. Given a set of user-specific pins as a query, Pixie selects in real-time from billions of possible pins those that are most related to the query. To generate recommendations, we develop Pixie Random Walk algorithm that utilizes the Pinterest object graph of 3 billion nodes and 17 billion edges. Experiments show that recommendations provided by Pixie lead up to 50% higher user engagement when compared to the previous Hadoop-based production system. Furthermore, we develop a graph pruning strategy at that leads to an additional 58% improvement in recommendations. Last, we discuss system aspects of Pixie, where a single server executes 1,200 recommendation requests per second with 60 millisecond latency. Today, systems backed by Pixie contribute to more than 80% of all user engagement on Pinterest.
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Can AI predict when that new hire will quit?

Can AI predict when that new hire will quit? | Social Foraging | Scoop.it
New pattern matching tech takes aim at predicting how long new hires will stay, potentially saving employers billions per year. But has AI really cracked the code on employee retention?
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Polisis AI Reads Privacy Policies So You Don't Have To

Polisis AI Reads Privacy Policies So You Don't Have To | Social Foraging | Scoop.it
YOU DON'T READ privacy policies. And of course, that's because they're not actually written for you, or any of the other billions of people who click to agree to their inscrutable legalese. Instead, like bad poetry and teenagers' diaries, those millions upon millions of words are produced for the benefit of their authors, not readers—the lawyers who wrote those get-out clauses to protect their Silicon Valley employers.

But one group of academics has proposed a way to make those virtually illegible privacy policies into the actual tool of consumer protection they pretend to be: an artificial intelligence that's fluent in fine print. Today, researchers at Switzerland's Federal Institute of Technology at Lausanne (EPFL), the University of Wisconsin and the University of Michigan announced the release of Polisis—short for "privacy policy analysis"—a new website and browser extension that uses their machine-learning-trained app to automatically read and make sense of any online service's privacy policy, so you don't have to.
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Closed-loop stimulation of temporal cortex rescues functional networks and improves memory

Closed-loop stimulation of temporal cortex rescues functional networks and improves memory | Social Foraging | Scoop.it
Memory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct brain recordings in humans. We apply targeted stimulation to lateral temporal cortex and report that this stimulation rescues periods of poor memory encoding. This system also improves later recall, revealing that the lateral temporal cortex is a reliable target for memory enhancement. Taken together, our results suggest that such systems may provide a therapeutic approach for treating memory dysfunction.

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Sidewalk Labs Is Building a Platform for Making the City of Tomorrow

Sidewalk Labs Is Building a Platform for Making the City of Tomorrow | Social Foraging | Scoop.it
The Alphabet company is the latest to offer an "operating system" for the age of urban mobility.
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Let's make this the year we reclaim control of our data

Let's make this the year we reclaim control of our data | Social Foraging | Scoop.it
We have always kept data about ourselves, from household accounts to lovingly kept records of our baby's height and weight. But when data like this is stored centrally it can be used to benefit lots of other people, too.
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The most important connection in any network is the local.

The most important connection in any network is the local. | Social Foraging | Scoop.it
Networks regulate everything from ant colonies and middle schools to epidemics and the internet. Here’s how they work
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MIT launches the MIT Intelligence Quest

MIT launches the MIT Intelligence Quest | Social Foraging | Scoop.it
At a time of rapid advances in intelligence research across many disciplines, the Intelligence Quest — MIT IQ — will encourage researchers to investigate the societal implications of their work as they pursue hard problems lying beyond the current horizon of what is known.
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Your brain reveals who your friends are: Study illustrates how similar neural responses predict friendships

Your brain reveals who your friends are: Study illustrates how similar neural responses predict friendships | Social Foraging | Scoop.it
You may perceive the world the way your friends do, according to a Dartmouth study finding that friends have similar neural responses to real-world stimuli and these similarities can be used to predict who your friends are.
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How Fast Is AI Progressing? Stanford's New Report Card for Artificial Intelligence

How Fast Is AI Progressing? Stanford's New Report Card for Artificial Intelligence | Social Foraging | Scoop.it
When? This is probably the question futurists, AI experts, and even people with a keen interest in technology dread most. It's been famously difficult to predict when developments in AI will take place. Stanford's new AI Index aims to clarify the situation by regularly defining and measuring AI progress.
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Deep Safety: NIPS 2017 Report - Future of Life Institute

Deep Safety: NIPS 2017 Report - Future of Life Institute | Social Foraging | Scoop.it
This year’s NIPS gave me a general sense that near-term AI safety is now mainstream and long-term safety is slowly going mainstream. On the near-term side, I particularly enjoyed Kate Crawford’s keynote on neglected problems in AI fairness, the ML security workshops, and the Interpretable ML symposium debate that addressed the “do we even need interpretability?” question in a somewhat sloppy …
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New algorithm for simulating the structure of quantum systems on a quantum photonic chip

New algorithm for simulating the structure of quantum systems on a quantum photonic chip | Social Foraging | Scoop.it
An international collaboration of quantum physicists from the University of Bristol, Microsoft, Google, Imperial College, Max Planck Institute, and the Sun Yat-sen University have introduced a new algorithm to solve the energy structure of quantum systems on quantum computers.

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Neural Responses To Music Show If You’re A Musician Or Not

Neural Responses To Music Show If You’re A Musician Or Not | Social Foraging | Scoop.it
Researchers in Finland predicted with significant accuracy if people were musicians or not, by applying methods of computational music analysis and machine learning, on brain imaging data collected during music …
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Job One for Quantum Computers: Boost Artificial Intelligence

Job One for Quantum Computers: Boost Artificial Intelligence | Social Foraging | Scoop.it
The fusion of quantum computing and machine learning has become a booming research area. Can it possibly live up to its high expectations?
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