One concern that often arises in statistics is erroneous signals. A small bias in a sensor, for example, can cause AI systems to see an effect that isn’t real. The likelihood of a system picking up on an errant signal rises with the volume of data collected; a tiny bias in a sample is far more likely to be noticed by AI when using the volume of data common with today’s machine learning systems. Even data of reasonably high quality can lead to erroneous results, potentially leading companies down an unproductive path. This is part of the reason why data scientists are in such high demand. Their ability to implement the right algorithms is clearly important, but it also takes human judgment to make sense of the results AI systems produce. Determining whether a signal is a real effect can be a challenging task. The power of machine learning is largely due to its ability to learn on its own. In order to get started, however, ML systems need to be trained with a set of data, and this data set needs to be of especially high quality, as even small problems can spoil the algorithms from the beginning.
Even though the vast majority of companies—91 percent—that use data and analytics have experienced increases in revenue, only a third see themselves as leaders in customer experience. This gap highlights how underutilized data and analytics continue to be in the business world. Researchers from the MIT Center for Digital Business define digital transformation as “the use of technology to radically improve performance or reach of enterprises.” In a 2014 survey of 157 executives at 50 companies, researchers found the best-performing companies combined digital activity with strong leadership to leverage technology for transformation. According to the researchers, these companies had reached digital maturity—a differentiator that led them to outperform their competition. The key areas where the MIT Center for Digital Business saw executives digitally transforming their processes were customer experience, operational processes, and business models. Additionally, as Forbes and Hitachi’s survey shows, these are also areas where IT leadership can lead the way. To be successful with digital transformation,
To continuously deploy to live users, organizations must consider the quality of the code and visibility into each update's effects. Testing should be part of a CI/CD strategy, but test is never an exact replica of production. "You can't replicate that scale, and you can't put customer data into a [traditional] staging environment," said James Freeman, head of professional services at Quru, a consultancy focused on open source technologies. Things test fine and pass to production, then they go live and fall over. "You've got to put good process behind deployments," Freeman said in a presentation at AnsibleFest 2018 in Austin, Texas. Ibotta uses blue/green deployment to handle the multitude of microservices updates per day. Blue and green setups mirror each other and trade off as staging and production environments. The team can quickly revert to a previous version of code without creating a bottleneck. The blue/green changeover currently serves as a gate between development/test and production.
To get the most out of a digital transformation initiative, an organization needs to commit to it for the long haul. It has to follow a plan, execute on specific goals, measure progress, incorporate feedback and keep improving, cycle after cycle, stage after stage. But to arrive at the project’s later stages, the organization has to get started. It needs to get buy-in for the project at all levels, and this needs to be driven by a hand-picked “adoption team.” Assembling the right people for this team can push a project well along the track. Picking the wrong people, or neglecting to create an adoption team at all, can doom the project before it gets out of the gate. What roles do the various members play? How do you find the right people? And how far should this team take the project before others move in to drive key aspects of the project in its later stages? Here are some thoughts to guide your digital transformation planning.
There were no additional details about the capabilities of this destructive “new generation of Stuxnet;” unsurprisingly, Israel’s Mossad intelligence agency refused to discuss if it played any role in the attack. Although Foreign Policy previously revealed how “botched CIA communications” ended up costing the lives of Chinese agents, Yahoo News reported that Iranian intelligence officials simply Googled to find the CIA’s communication channel; via Google, Iran reportedly found numerous websites used by the CIA as covert communications channels which led to Iran rounding up 30 people earmarked as CIA spies. 30 more people recruited as CIA agents in China were killed after China allegedly did some Googling to find secret CIA websites which acted as “transitional” communications.Those compromised sites on the web, which had been indexed by Google, may have also “endangered all CIA sources that used some version of this internet-based system worldwide.”
The not-so-good news is that Canada and its startup cities are losing ground to startup hubs such as New York and London; Beijing and Shanghai; Bangalore and Mumbai; Berlin, Amsterdam, Stockholm, and Tel Aviv. More worrying, Canada is failing to take advantage of the United States’ weakening position, which is attributable in part to its tighter immigration policies. While the U.S. continues to generate the largest amount of startup and venture capital activity, its share of the global total has been falling steadily, from more than 95 per cent in the mid-1990s to about two-thirds in 2012, and a little more than half today. But the country that has gained the most ground is China, which now attracts nearly a quarter of global venture capital investment. Exactly why Canada is lagging is unclear. A growing number of Canadian commentators suggest that the influx of large U.S. and Asian tech firms into Canada is sucking up tech talent that would have otherwise gone to local start-ups.
A firewall is a network device that monitors packets going in and out of networks and blocks or allows them according to rules that have been set up to define what traffic is permissible and what traffic isn’t. There are several types of firewalls that have developed over the years, becoming progressively more complex over time and taking more parameters into consideration when determining whether traffic should or should not be allowed to pass. The most modern are commonly known as next-generation firewalls (NGF) and incorporate many other technologies beyond packet filtering. Initially placed at the boundaries between trusted and untrusted networks, firewalls are now also deployed to protect internal segments of networks, such as data centers, from other segments of organizations’ networks. Firewalls are commonly deployed as appliances built by individual vendors, but they can also be bought as virtual appliances – software that customers install on their own hardware.
“The first thing we do, let’s kill all the lawyers.” This declaration from Shakespeare’s Henry VI is made by Dick the Butcher, a gang member plotting to overthrow the King of England who is afraid the honorable lawyers might gum up the works. I was recently reminded of this line when a startup I invested in was acquired and the company’s founder shared with me that he was aghast at the legal bureaucracy he encountered at his new parent corporation. The lawyers were not adept at delivering speedy, practical solutions, and the founder was forced to spend far too much time micromanaging or working around them. This mismatch is hardly unique. Over the past few years, several well-funded startups have pursued a get-big-fast strategy to maximize early-mover advantages. But when there is a rush to hire throughout the organization, a company can easily end up with lawyers who, by nature or training, are ill-suited to its particular business climate.
"We've seen a lot of destruction of log data, very meticulous clean-up of antivirus logs, security logs, and denying IR teams the access to data they need to investigate," an IR professional said. In fact, according to the Carbon Black report, 72 percent of all its partner IR professionals saw counter-IR operations in the form of destruction of logs, which appears to have become a standard tactic in the arsenal of most hackers. But in some cases, hackers took log destruction and other counter-incident response operations to a new level, and in some cases, their actions resulting in more lasting damage. "Our respondents said victims experienced such attacks 32% of the time," Carbon Black said in its report. "We've seen a lot of destructive actions from Iran and North Korea lately, where they've effectively wiped machines they suspect of being forensically analyzed," an IR professional said.
Constraints and bottlenecks can be discovered anytime before, during or even after the sprint. Some examples may be cross-departmental involvement, governance structures, approval boards, brand restrictions, finance or legal approval, etc. The list is long, and the sprint process can be adapted to your context, but I’d caution against doing so just to avoid conflict. Some healthy conflict of ideas may be necessary to improve your organisation’s responsiveness. ... This revelation was counter to the traditional belief that you start by changing culture in order to affect behaviour. In addition, Rita Gunther McGrath, author of The End of Competitive Advantage and an authority on strategy, innovation and entrepreneurship, has highlighted that the key for management in the digital era is the ability to experiment and to rapidly learn from those experiments. Considering all human systems are complex adaptive systems, viewing any organisational change efforts through the lens of Dave Snowden’s Cynefin framework would certainly support an experimental, probe-sense-respond approach.
Quote for the day:
"Don't blow off another's candle for it won't make yours shine brighter." -- Jaachynma N.E. Agu