Deep learning certainly involves training carefully designed deep neural networks and various design decisions impact the training regime of these deep networks. Some of these design decisions include Type of network layer to use such as convolution layer, linear layer, recurrent layer, etc. in the network, and how many layers deep should our network be? What kind of normalization layer we should use if at all? What should be the correct loss function to optimize for? Majorly these design decisions depend upon the underlying task we are trying to solve and require a deeper understanding of the different options we have at hand. In this post, I will focus on the second point “different Normalization Layers in Deep Learning”. Broadly I would cover the following methods. ... One important thing to note is, in practice the normalization layers are used in between the Linear/Conv/RNN layer and the ReLU non-linearity(or hyperbolic tangent etc) so that when the activations reach the Non-linear activation function, the activations are equally centered around zero. This would potentially avoid the dead neurons which never get activated due to wrong random initialization and hence can improve training.
Certain web sites require the user to enter a security question and an answer for it. The list of questions is standard, and one of them usually is – “What is your mother’s maiden name?”. This form of knowledge-based authentication is one of the most important aspects of conducting successful transactions online for high-value products, as most banks ask this as a security question for making any changes to the account. ... Credit card dumps are used by fraudsters to capture valuable card data such as the card number and expiration date. These can be obtained in a number of ways. The most popular method nowadays is the “skimming”, a process in which an illegal card reader is used to copy the data from a Credit Card. Other methods include hacking into a retailer’s network or when unknown to the retailer, a malware-infected point-of-sale device sends information to cybercriminals.... Bank Identification Number is the first six numbers that appear on a Credit Card, and it uniquely identifies the institution issuing the card. The BIN is key in the process of matching transactions to the issuer of the charge card. This numbering system also applies to charge cards, gift cards, prepaid cards and even electronic benefit cards.
Interestingly, the operators do not appear to be utilizing any actual ransomware payload in their attacks. It begins by brute forcing weak password protocols for MySQL databases, followed by collection of data on existing tables and users before installing a hidden backdoor on the way out to facilitate future break-ins. “By the end of execution, the victim’s data is gone – it’s archived in a zipped file which is sent to the attackers’ servers and then deleted from the database,” write authors Ophir Harpaz and Omri Marom. Guardicore Labs also spotted two distinct versions of this campaign. The first, between January and November 2020, composed roughly two-thirds of observed attacks and involved leaving a ransom note with a Bitcoin wallet address, a ransom demand, an email address for technical support and a 10-day deadline for payment. However, in leaving those breadcrumbs, the operators made it possible for researchers to poke around their Bitcoin wallet and examine how much money had been transferred to it. Ultimately, they traced nearly $25,000 in payments from four separate IP addresses.
Multicloud also presents a second alluring possibility, an extension of that original cloud-native logic: the ability to abstract cloud computing architectures so they can port automatically and seamlessly (if not just quickly) between cloud providers to maximize performance, availability, and cost savings—or at least maintain uptime if one cloud vendor happens to goes down. Cloud-agnostic platforms like Kubernetes, which run the same in any environment—whether that’s AWS, GCP, Azure, private cloud, or wherever—offer a tantalizing glimpse of how companies could achieve this kind of multicloud portability. But while elegant in theory, multicloud portability is complicated in practice. Dependencies like vendor-specific features, APIs, and difficult-to-port data lakes make true application and workload portability a complicated journey. In practice, multicloud portability only really works—and works well—when organizations achieve consistency across cloud environments. For that, businesses need a level of policy abstraction that works across said vendors, clouds, APIs, and so on—enabling them to easily port skills, people, and processes across the cloud-native business. While individual applications may not always port seamlessly between clouds, the organization’s overall approach should.
Most organizations understood the innate value of employee well-being, which is defined in the report by a five-point system of indicators, all of these at work: Feeling calm, feeling energized, rarely feeling overwhelmed by responsibilities, feeling positive about yourself, and having trusting relationships Employee well-being remains critical as organizations continue to recover from this time of disruption, said Lauren Rice, XM scientist, Qualtrics, also in the report. "Whether it's providing flexibility to employees as they juggle work and personal responsibilities, supporting employees as they attend to any family health concerns, or just taking the time to listen to employees' concerns, it's a necessity at this time for organizations to care and support employees' well-being. When organizations care for their employees, the employees will in turn show care and dedication to their work and the organization." ... There's a great disparity between employers and their staff, according to the report, regarding acting on feedback: 92% of employees believe it's important the company listen to feedback, but admit that only 7% of employees say their company does so.
The first problem seems to be the quality and the processes used in data storage. We like to celebrate how much we have, but data normally comes from separate systems, measured in different ways, stored in different places. Most CTOs will embarrassingly admit they have too much data these days, not too little. They find the data dirty, contradictory and in systems that won’t mesh. If companies know that much about everything, why are we sent credit card offers for credit cards we already have? Why is my bank offering me cheap loans and pitching me funds to invest in at the same time? ... Big data has the temptation of making the complex seem simple. It may think I like certain movies, when in fact I like certain movies at certain times or in certain situations. The crap I watch after a beer on a plane ruins any algorithm’s chances, let alone an Airbnb guest using my TV. We endlessly refer to “data-driven” insights when I’ve only ever seen facts, not insights, from data. Insights are found by observation and, where needed, supported by data. No spreadsheet ever revealed anything as beautiful and transformational as an insight.
The remote work experiment seemed to offer an initial boost in productivity. But sustaining such productivity has been difficult, in part because the home wasn’t designed for work and the consequences of “Zoom” fatigue are real. Indeed, emerging evidence suggests burnout is plaguing remote workers across the board. Yet managing employee burnout is particularly difficult during a pandemic, when people are asked to mostly isolate at home, away from colleagues whose mere presence can often ease work-related stress. ... What’s worse, corporate policies meant to monitor and control employee behavior – whether while they work remotely or as means to make the office safer – risk eroding worker trust and undermining cultural norms. And the impact of these policies will likely endure long after the crisis subsides ... A third major cost of this sustained remote period of work is the lack of collaboration and its disruptive impact on innovation. Sure, some collaborations and idea generation can take place via Zoom meetings, but innovation still largely happens in physical spaces: at lab benches, alongside a 3D printer or in unintended office interactions that spark interdisciplinary collaborations.
Times changed and so did the use of technology in the legal sector. Although, there is no doubt that technology in the legal sector has improved efficiency, reduced errors and has further demystified the operations of the court system, but the growth has been slow. Perhaps, because the traditional legal system is a relic of the past, which while adjusting itself to the modern world technology is still, metaphysically, attached to its ancient and archaic roots. The present-day legal system, which has been slow in keeping up with the changes in technology, has for the very first time attempted to digitise itself overnight during these unprecedented pandemic times. Virtual court hearings and paperless filings, even with certain limitations, has been welcomed by the legal sector. The credit for the digitisation of courts should be given to the Supreme Court’s e-committee headed by Hon’ble Justice DY Chandrachud. The e-committee by swiftly implementing a contingency plan has enabled our courts to continue operating even during this pandemic thus helping thousands to get justice. However, the growth should not stop here and this opportunity should also be fully utilised to explore other technological innovations which can be imbibed and integrated into the prevalent legal tech.
Attackers could gain access to the devices to manipulate them in one of two ways. Either they're able to physically gain access to the PoS terminal, or they're able to remotely gain access via the internet and then execute arbitrary code, buffer overflows and other common techniques which can provide attackers with an escalation of privileges and the ability to control the device – and see and steal the data that goes through it. Remote access is possible if an attacker to gains access to the network via phishing or another attack and then move freely around the network to the PoS terminal. Ultimately, the PoS machine is a computer and if it's connected to the network and the internet, then attackers can attempt to gain access to and manipulate it like any other insecure machine. The way the PoS terminal communicates with the rest of the network means attackers could access unencrypted data card data including Track2 and PIN information, providing all the necessary information required to steal and clone payment cards. In order to protect against attacks exploiting PoS vulnerabilities, it's recommended that retailers using the devices ensure they're patched and up to date and they should avoid using default passwords where possible.
The first step is to observe. Places to look for indications of core culture are in the mission statement, in vision documents, and posters put up by the Human Resources department. Since culture is driven at the leadership level, observe what leadership values and rewards. In a more formal process, surveys of staff and leadership, past and present, can provide knowledge useful for determining the company culture. Recognize that culture clash is a possibility with mergers and acquisitions. In those situations, “Make sure that you have those conversations at your executive level because you can’t really drive that through your Data Governance programs,” Levins said. ... Although most companies have a predominant core culture, and there are often subcultures within that culture, Levins said, but for the purpose of the presentation, they would be focusing on the core culture for the organization as a whole. Each culture has strengths and pitfalls. Elder noted, “The things that we love about our partner also drive us crazy sometimes.” ... Cultivative culture is focused on people and possibility, said Elder. “How can we make the future better? How can we make people better?”
Quote for the day:
"Added pressure and responsibility should not change one's leadership style, it should merely expose that which already exists." -- Mark W. Boyer