February 14, 2015

Our Fear of Artificial Intelligence
The question “Can a machine think?” has shadowed computer science from its beginnings. Alan Turing proposed in 1950 that a machine could be taught like a child; John McCarthy, inventor of the programming language LISP, coined the term “artificial intelligence” in 1955. As AI researchers in the 1960s and 1970s began to use computers to recognize images, translate between languages, and understand instructions in normal language and not just code, the idea that computers would eventually develop the ability to speak and think—and thus to do evil—bubbled into mainstream culture.

Hyperloop Is Real: Meet The Startups Selling Supersonic Travel
You remember the hyperloop, don’t you? It’s that far-out idea billionaire industrialist Elon Musk proposed in a 58-page white paper in August 2013 for a vacuum-tube transport network that could hurtle passengers from San Francisco to Los Angeles at 760 miles an hour. Laughed off as science fiction, it is as of today an actual industry with three legitimate groups pushing it forward, including Hyperloop Technologies, the team in Harry Reid’s office. They emerge from “stealth” mode with this article, armed with an $8.5 million war chest and plans for a $80 million round later this year. “We have the team, the tools and the technology,” says BamBrogan. “We can do this.” The 21st-century space race is on.

Three Key Disruptors to Business as Usual!
The internet of everything is transformational because it is creating an ‘explosion of connectivity!’ This potentially makes it possible for governments, organizations and businesses to invent and innovate with unlimited access to global connectivity. The internet of everything connects People, Things, Processes and Data, in ways that enables us to take Data to create Knowledge, Wisdom and Business. ... One of the key questions is how can we use entrepreneurship to break the ‘education-work-employment’ paradigm? How can we to teach the one quarter of the world’s youth who are neither studying nor working (as well as the growing more mature jobless generation) how to take personal responsibility for creating their own futures by adopting an entrepreneurial mindset?

What Do I Do With All This Data?
Before you can even begin thinking about implementing a big data solution – what do you do with the data you already have? Or maybe you are dabbling in digital marketing and social media on some level, but meanwhile, your data continues to pile up without any real insights into what it is telling you. If any of this sounds familiar, read on as we share some practical tips on how to better manage “all that data”. ... As part of any new data initiative, a business needs analysis should also be performed to understand what is required of data moving forward. A business needs analysis focuses on understanding business objectives, strategic goals and business drivers.

Big data digest: The backlash begins
The problem, according to Science News, is one of validity. With so much data and so many different tools to analyze it, how can one be sure results are correct?“Each time a scientist chooses one computer program over another or decides to investigate one variable rather than a different one, the decision can lead to very different conclusions,” Tina Hesman Saey wrote. The validity problem is not one faced only by big data enthusiasts, but by the science community in general. In an earlier article, Science News tackled the issue of irreplicable results, or the increasing inability of scientists to reproduce the results from previously published studies.

Automating the Data Scientists
Computers have made it trivial to run complex mathematical operations on large collections of data, and selling data analysis software is a growing business. But human creativity and expertise is still needed to choose and deploy the methods that can explain the patterns in a data set. The automatic statistician is one of a handful of tools being built to automate some of that expertise. When the system was given a decade of data on air travel, for example, it produced a nine-page report with four mathematical explanations for trends seen in the data that could be used to produce forecasts.

How to Help Millennials Shine in the Workplace
This is the millennial generation’s moment in the hot seat. Millennials are often viewed as impatient, tech-obsessed and disloyal to their employers, but while the specifics may be different, each generation has been in this position before: You’re new to the workforce, you have new ways of working and businesses can’t quite figure out how to deal with you. “Each generation had a different backdrop,” says Gloria Larson, president of Bentley University. Millennials, like every other generation, are “a group that is facing the realities of the decades they grew up in,” she says.

Object Pool Design Pattern
Object pools (otherwise known as resource pools) are used to manage the object caching. A client with access to a Object pool can avoid creating a new Objects by simply asking the pool for one that has already been instantiated instead. Generally the pool will be a growing pool, i.e. the pool itself will create new objects if the pool is empty, or we can have a pool, which restricts the number of objects created. It is desirable to keep all Reusable objects that are not currently in use in the same object pool so that they can be managed by one coherent policy. To achieve this, the Reusable Pool class is designed to be a singleton class.

Application Security for Agile Projects
Leaving requirements like security until the end can be detrimental, but making certain decisions too early can also cause problems. Software architecture covers many of the cross-functional requirements of your application like performance, scale or security. These requirements are often discussed and decided upon before you have written a line of code. This is when you know the least. Architectural decisions made at the very beginning of an engagement can lead to security issues, because we don’t have all the information we need to make the right decision. By the time security vulnerabilities are uncovered, it might be too late to change the architecture.

'Governance by exception' are current board processes too slow?
As technology has become integral to modern organisations, enterprise technology governance has become integral to corporate governance. And here's where the increasing risks lie and why we're starting to see board fiduciary responsibility challenged in relation to technology. Boards continue to recruit people with the same competencies - mostly finance and legal + industry experience. That increases a key aspect of competency risk. The knock-on effect flows into areas such as security risk, infrastructure, competitive and reputational risks. Think Sony and how hackers shut it down. Think about the growing number of once iconic brands that have gone out of business or lost significant market share because they simply didn't keep up with technology-driven change in their sector.

Quote for the day:

"Keep your fears to yourself, but share your courage with others." -- Robert Louis Stevenson

No comments:

Post a Comment