Today, hacking has evolved into a wide-ranging web of cybercrime that is hard to avoid, with perpetrators carrying out their misdeeds for a variety of motives – selling data for profit, hacktivism, stealing state secrets, and revenge against former employers or enemies. But make no mistake, the prime motive is profit. The cost of cybercrime will top $2 trillion by 2019, according to Juniper Research. ... Hacking is a fact of life and it’s only going to become more widespread. The sooner we accept that, the better we can defend ourselves. Pretending it doesn’t exist, that it’s somebody else’s problem or some technical genius somewhere will come up with a silver bullet against cybercrime is unrealistic and dangerous. Everyone has a responsibility to defend against cybercrime because it affects us all.
We need to re-address how corporations are using the startup model for their own innovation efforts. As the last few years have seen inadequate responses from different types of accelerators (an outside entity that assists the corporate’s startup efforts) and incubators or innovation labs (that are owned by the corporate), we are re-entering testing mode with corporate innovation once again. Now is the time to create an optimal new approach. As with each in-vogue wave, there is preaching and swallowing without really understanding what something is, when to use it and how to really do it. In the application of lean startup, the emphasis has been on “build, measure, learn,” and this mantra has been used as justification to start with building an un-validated hypothesis (read: gut-feeling ideas not based on any customer insight, aka mud). The focus is on speed while customer research and learning is often lost from sight.
In India, early-stage internet of things architectures were becoming apparent. Dot-matrix displays could be set up in small towns stating when the travelling doctor would visit next. Details of how to book an appointment could be included — a simple text message. The patient could then be sent reminders as the date became closer — cutting down on missed appointments and wasted time. All this seemed to get me noticed, and I was invited to become a Fellow of the Royal Society for the encouragement of Arts, Manufactures and Commerce (RSA). This 260-year-old institution works to enrich society through ideas and action. The RSA stands for everything I believe in. It is looking at how the world can be made into a better, fairer place; in how those who are the ‘haves’ can better help those who are the ‘have less.’
While the technological components that make up the foundation of Industry 4.0 are many– robots, big data, augmented reality, cloud computing, cyber security, additive manufacturing, system integration etc., AIM explores how IoT is playing an important role in the fourth industrial revolution. Intelligent connectivity of devices has made is easy for objects to communicate in a way like never before. Not just at an individual level, but manufacturing companies are keenly implementing this intelligent connectivity of smart devices in factories and shops. By combining the physical, virtual, IT and cyber-system worlds, manufacturers are aiming to transform into “smart factory operators”, who can manage highly automated, connected equipment and analyse data provided by the systems. In other words, it is set to create a new working environment of integrated productivity between worker and machine.
The naked algorithms themselves are unlikely to provide an edge. Many of them are in the public domain, and businesses can access open-source software platforms, such as Google’s TensorFlow. OpenAI, a nonprofit organization started by Elon Musk and others, is making AI tools and research widely available. And many prominent AI researchers have insisted on retaining the right to publish their results when joining companies such as Baidu, Facebook, and Google. Rather than scrap traditional sources of competitive advantage, such as position and capability, AI reframes them. (See Exhibit 2.) Companies, then, need a fluid and dynamic view of their strengths. Positional advantage, for example, generally focuses on relatively static aspects that allow a company to win market share: proprietary assets, distribution networks, access to customers, and scale. These articles of faith have to be reimagined in the AI world.
Knowledge is the hard part. It’s taking that data and turning it into something meaningful. It’s converting an avalanche of data into action-oriented insights. That’s the hard part. How do you turn data into knowledge? That’s where business intelligence (BI) comes into play. BI is the process of turning unusable data into actionable insights. When done correctly, BI will improve visibility, provide insights into customer behavior, improve efficiency, and so much more. How can you get the most out of your BI investment? I won’t get into the details here, as it’s a topic covered in a previous article. But, I would like to add one point: To truly get the most out of BI, it’s important that you stay ahead of the curve. The world of BI is constantly changing. New tools emerge. New trends take hold. If you can stay ahead of the curve, you’re better positioned to turn your data into knowledge–and a competitive advantage.
Executives do not realize that a major threat to their company’s security is social engineering, which refers to the psychological manipulation of users who unknowingly divulge confidential information. Cybercriminals can use tricks to gain the confidence of company employees and partners. The goal is usually to execute a larger -- and more complex -- fraudulent transaction. The problem is not the use (or lack) of security tools and technology, but rather employees who are unknowingly the objects of security threats. The latest trick employed by criminals is to emulate executives within a company in a trusted environment. For example, an employee receives a legitimate-looking email from the CEO or CFO, instructing them to wire money. Before, employees used to be able to tell if the email was real, but today, employees are often duped by sophisticated hackers.
Elemental Cognition's technology seems to be aimed at the problem of going beyond the simple recognition/response models that dominate the A.I. landscape right now. I suspect Ferrucci is building out a technology that will combine outputs of deep learning and other machine-learning systems with the ability to draw inferences from, reason about and support decisions using the facts that they generate. I have faith in Ferrucci for a very specific reason: He is less a scientist and more an engineer. His history at IBM was one of building toward the solution rather than in service of a theory. He succeeded in building a system that leveraged existing technologies, but was built in such a way that it did the job at hand and did it exceedingly well.
Overall, the results show "an interesting disparity between the views of C-level respondents and those of IT decision makers," said Kevin Taylor, managing director at BAE. "Each group's understanding of the nature of cyber threats, and of the way they translate into business and technological risks, can be very different." ... The survey lends support to the opinions of other analysts who say C-level executives need to get more informed on cybersecurity threats. Tom Ridge, former secretary of Homeland Security, recently urged CEOs and corporate board to increase their level of cyber-risk awareness. "Cybersecurity is the most significant governance challenge for the public and private sector," Ridge said in a recent interview. "It's not just the exclusive domain of the CIO and CTO, and is now in the domain of the CEO and the corporate board."
Overall, the cybersecurity industry is progressing with its R&D efforts in order to come up with solutions that will alleviate various security challenge pain points. If everyone involved is committed to fixing the problem, then developing new technologies with built-in security features will become the norm and the result will be a much safer IoT. With the emergence of software-defined technology, tight security protocols and encryption can be implemented at the fraction of the cost of hardware components. Vendors should consider de-commoditizing and coming up with a more differentiated product offering that, for example, includes security features. It’s obvious that these features come with a price tag. However, only when vendors translate these features into tangible benefits will consumers be prepared to pay a higher premium.
Quote for the day:
"For success, attitude is equally as important as ability." -- Harry F. Banks