Wikipedia's no-cost version for people without mobile data plans is dead
- The Wikimedia Foundation has killed off Wikipedia Zero, an initiative to deliver the online encyclopedia at no charge to mobile users around with the world.
- The zero-rated service was launched back in 2012 and saw the nonprofit partner with mobile carriers to waive the cost for accessing Wikipedia; it was available through 97 mobile operators in 72 countries, with a cumulative 800 million subscribers.
- The other reason is actually a sign of change for the better: mobile data costs have been dropping in the past few years.
- While India’s Aircel carrier signed on to offer Wikipedia Zero to its 60 million subscribers back in 2013 without much of a fuss, Facebook found its Free Basics zero-rated service banned in the country following backlash from critics who were concerned about it becoming a gatekeeper that could control what information and services internet first-timers would be able to access.
Westpac banks on AI advances as automation and cognitive systems mature
- The bank's general manager of technology applications development, Tim Whiteley, said that, while he expected the rapidly evolving technology to change the nature of doing business, there was still years of work to do to train software to work properly.
- Customers are also dealing with AI-enabled chatbots based on work with IBM's Watson in its contact centres and Mr Whiteley said AI would be phased in across the bank steadily over the coming years.
- Under chief information officer Dave Curran, Westpac has overhauled the bank's internal systems in a way that makes it easier for it to track and deal with individual customers, regardless of the technology platform they use to interact with it.
- Mr Whiteley said he believed that the nature of work being conducted by humans would change, and that Westpac had begun working on programs that would reskill its own staff for future jobs.
How To Track Elon Musk's Roadster On Its Journey Towards Mars
- If you’re curious what that path looks like, an aerospace engineer and SpaceX admirer has put together a website that uses NASA data to track the Roadster’s course.
- It’s called Where Is Roadster?, and it’s fascinating, with both live data on the Roadster’s location and an interactive tool that shows its future course.
- But the Roadster, like all things in the galaxy, is subject to the tug of gravity, so instead of a straight path, it’s tracing a long arc away from Earth and the sun.
- After that, the Roadster will actually return to something close to Earth’s orbit, though again, Earth itself won’t be anywhere close.
- According to the site’s data, which is taken from NASA’s Jet Propulsion Laboratory, the Roadster won’t actually be close to Mars until early October of 2020.
Rochefort – Poor Man's Kafka
- You can lose data on crash and there is no replication, so you have to orchestrate that yourself doing double writes or something.
- The super simple architecture allows for all kidnds of hacks to do backups/replication/sharding but you have to do those yourself.
- My usecase is ok with losing some data, and we dont have money to pay for kafka+zk+monitoring(kafka,zk), nor time to learn how to optimize it for our quite big write and very big multi-read load.
Quasistatic Cavity Resonance for Ubiquitous Wireless Power Transfer
- We introduce quasistatic cavity resonance (QSCR), which can enable purpose-built structures, such as cabinets, rooms, and warehouses, to generate quasistatic magnetic fields that safely deliver kilowatts of power to mobile receivers contained nearly anywhere within.
- These oscillating currents in turn generate magnetic fields that permeate the interior of the structure, thus enabling wireless power transfer to receivers contained within, while simultaneously isolating the potentially harmful electric fields in capacitors.
- This high Q-factor structure efficiently stores electromagnetic energy, and the discrete capacitors allow the resonant frequency to be lowered to a point where the cavity enters the deep sub-wavelength regime, effectively separating the magnetic field from the electric field.
- By scaling the quasistatic cavity resonator up to the size of a living room, office, or warehouse it is possible to deliver safe and ubiquitous wireless power to small mobile devices contained nearly anywhere within.
Turning big data into sound
- Ivica Ico Bukvic, associate professor of composition and multimedia in the College of Liberal Arts and Human Sciences, and Greg Earle, professor of electrical and computer engineering, used unique infrastructure provided by the Institute for Creativity, Arts, and Technology to investigate how immersive sound can be used to develop a better understanding of complex systems.
- This merging of technology and nature could further current analysis techniques and foster new breakthroughs involving complex systems in science, with the potential to produce new technologies designed to spur creativity,” concludes Dr. Bukvic, who says that if this approach to experiencing data can be proven to improve people’s understanding of complex relationships in physical systems, it could be applied to other fields of study: “It could have applications to fields such as thermodynamics, quantum mechanics, and aeronautical engineering; help advance visualizations and virtual reality systems; and create interdisciplinary bridges between scientific communities, including music, computing, and the physical sciences.
Introduction to Apple WatchKit with Core Motion – Tracking Jumping Jacks
- The ultimate goal is to build a machine learning model that can automatically categorize and log an exercise from the motion data we collect from the watch.
- In this post, we’ll focus on data collection by understanding Core Motion and building a WatchKit app to record jumping jacks.
- We’ll use this project as a starting point but before we start editing it, let’s first decide how we’re going to process the motion data from the watch.
- Looking at the data we’ve captured, it’s clear that there are distinct patterns that describe motion of a jumping jack in 3D space.
- In the next post, we’ll use machine learning to classify exercises for us and explore the different tradeoffs we need to make so our model runs on mobile.
As smart contracts get smarter, the rules of development will change
- Blockchain projects like Chronicled and Qtum already support access to trusted off-chain data sources (“oracles”) and Internet of Things (IoT) sensors to allow off-chain events to trigger clauses in smart contracts.
- And each additional line of code carries with it an additional portion of risk: that between business case and code, some meaning has been lost; that the smart contract will not execute as the developer intends or as the business stakeholder demands; and that money will be irretrievably lost.
- Current smart contracts cannot handle the large volumes of data from multiple different “oracles” that is needed to automatically execute complex agreements.
- Instead, IBM and Maersk, and anyone else wanting to exploit the convergence of IoT and blockchain, will need to build these new, more complex smart contracts from scratch.
For AI to thrive, it must explain itself
- The invention of deep learning, a technique which uses special computer programs called neural networks to churn through large volumes of data looking for and remembering patterns, means that technology which gives a good impression of being intelligent is spreading rapidly.
- Specifically, they emulate the way neuroscientists think that real brains learn things, by changing within themselves the strengths of the connections between bits of computer code that are designed to behave like neurons.
- But civilian programmes are also trying to give neural networks the power to explain themselves by communicating their internal states in ways that human beings can comprehend.
- The program does this by drawing on the assistance of a second neural network which has been trained to match the internal features of the agent doing the recognising (ie, the pattern of connections between its “neurons”) with sentences that people have written, describing what they see in a picture being examined.
Finger exercises: Caesar cipher (in elixir)
- Elixir is a lot of fun but it is a very spartan language.
- It has fewer data types and the usual iteration constructs are slightly disguised because it is a functional language.
- Instead of loops we have recursion and instead of list comprehension and other iteration constructs we have the pipeline operator (|>) and the Enum module for performing operations on data types that support the Enumerable protocol.
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