The transition to the era of the smartphone and mobile internet has allowed two companies — Apple and Google — to establish market dominance with their own proprietary ecosystems, including their respective app stores. As the new distribution model for software and digital content, the app stores have centralised the vast majority of mobile revenue streams within Apple’s and Google’s platforms. This change from the open web to privately managed walled gardens is amplifying global power imbalances, resulting in lower rates of participation and value capture by producers from marginalised geographies and socio economic backgrounds. The result: polarised opportunity between high- and low-income countries, with lower-income countries only earning an estimated 1% of global app economy revenues.
"They're not going to talk to the jailbreak crowd," Zdziarski said, referring to hackers who look for iOS vulnerabilities that can be exploited to let users add unsanctioned apps to an iPhone. He said that he and other reputable researchers had been turned away by the FBI when they volunteered to help. If they met a blank wall, jailbreak artists would have gotten nowhere, he reasoned. Other avenues, such as "de-capping," a term used to describe a tear-down of the iPhone's processor using acid and lasers, were also out, Zdziarski said, because they risked destroying the very thing the FBI claimed it needed, the data on Farook's phone.
The payoff comes from insights gleaned from collecting large amounts of various kinds of data and analysing them to uncover hidden patterns, correlations and other insights. Machine learning software can drill down into the data to discover and analyse factors determining the profit and loss for a product, supplier, and their customers. We can also see into the future, making better predictions and decisions. The result is that “quantitative change becomes qualitative”, as described by Steve Lohr in his best selling book Data-Is m”. Big data brings technology and the economy together. The benefits of a data-driven economy are obvious enough that we should all embrace the concept. For both technology companies and business firms, the market is just around the corner.
Vanguard's financial simulation software, essentially a predictive analytics tool that runs 10,000 simulations in under than a second, forecasts future returns and generates a set of outcomes over many time horizons. The client monitors the performance of their assets as well as progress toward their goals; the human advisor reviews and rebalances their portfolio to keep them aligned with those goals. While some software robots learn by inference, their improvisational capabilities remain limited. That's where the humans come in. Marcante says the advisor also helps clients avoid making trading errors during emotional times and volatile markets, often "talking them off the ledge when the markets are down and they're supposed to be holding long-term."
How big is the data science skills gap? There are several ways to attack that problem, and a number of smart people at renowned organizations have attempted to put numbers to the problem. Back in 2012, the research firm Gartner said there would be a shortage of 100,000 data scientists in the United States by 2020. A year earlier, McKinsey put the national gap in data scents and others with deep analytical expertise at 140,000 to 190,000 people by 2017, resulting in demand that’s 60 percent greater than supply. In 2014, the consulting firm Accenture found that more than 90 percent of its clients planned to hire people with data science expertise, but more than 40 percent cited a lack of talent as the number one problem.
TensorFlow is on the academic or research side of machine learning at Google. Machine learning APIs are on the opposite side of that spectrum and require much less understanding of machine learning to implement within an application. Cloud Machine Learning, announced Wednesday, is in the middle and can extend to either side. Ferraioli said developers can use Cloud Machine learning "When you have a customized problem that you want to solve." Cloud Machine Learning is a fully managed service, and developers can train it using a custom TensorFlow graph. It offers batch and online prediction at scale and an integrated Datalab experience, but regression and classification are its two primary tasks.
A smart home will have between 100 and 200 connected devices. How are you going to power them all? You can’t give each a battery. You’ll need energy harvesting for this. The markets are evolving so chipsets can use energy harvesting, but that’s not available to Bluetooth yet. ... Top-down creation of a smart city may be a bit too ambitious. But building a smart home, and extending the conversations of the intelligence washing machine and solar panels with the utilities, so they interact with the grid and the sewage systems with maximum efficiency, could be a way of building a smart city by increments, from the bottom up. ... The APIs that the manufacturers will have to offer in order to create interoperability will open the gate to all that information.
One is that if fast and reliable ongoing updates are important to you -- and, let's be honest, they probably should be -- you should pick a phone that's known to provide that feature. Google's Nexus devices are the safest bet, as they receive software directly from Google without any third-party interference or delays. Whether we're talking about security or broader system-level improvements, that's an extremely valuable assurance to have. Second, as we've been discussing, remember that updates on Android really aren't the same as updates on other platforms. Google knows about the challenges created by its open source setup, and that's why it's taken steps to create all the other methods of reaching users directly -- both via the security-oriented paths we've been discussing and via the company's ongoing deconstruction of Android.
It won’t just be fridges; we’ll see home energy systems, security devices, entertainment products, games, interactive wearables -- the list goes on and on. The question is, is it really going to happen? And shouldn’t we be seeing greater market penetration than we already do? While the IoT is a hot topic right now, we don’t have the sort of everyday uptake internet experts have predicted. In the grand scheme of things, there really aren’t very many connected watches, thermostats, or accessories. ... This article will look at the things the IoT needs to be on the forefront of the consumer experience, including the value to the consumer, the necessity of a centralized IoT platform, a set of international communication protocols, user education and greater security.
Quote for the day:
"Bad companies are destroyed by crisis, good companies survive them, great companies are improved by them." -- A Grove