August 08, 2022
Kannan Subbiah
FCA | CISA | CGEIT | CCISO | GRC Consulting | Independent Director | Enterprise & Solution Architecture | Former Sr. VP & CTO of MF Utilities | BU Soft Tech | itTrident
The Supreme Court decision pushed data privacy discussions to the forefront once more, says Christine Frohlich, head of data governance at Verisk Marketing Solutions. “Those of us who have been working in the data industry have been thinking about this for a long time,” she says. “The regulations we’re seeing in California, and now what we’re seeing in Colorado, Connecticut, Virginia, and Utah have made this a real hot topic within our industry.” Companies have a fundamental responsibility, Frohlich says, to protect consumer privacy to the best of their ability. Customers may enjoy personalized experiences such as a digital interaction with a brand or having products marketed to them in a personal way, but she says they are also concerned about how their data is used. Federal legislation on data privacy might move forward faster in response to the Supreme Court decision, Frohlich says. The “right to be forgotten,” or a deletion requirement is flowing through state legislation and what is being proposed potentially on a federal perspective, she says.?
Putting purpose over profits requires fintech innovation to have some social purpose other than making money and just being a ‘good’ fintech, and we know that consumers are now actively looking for this purpose when choosing their financial institution. At the same time, modern consumers value experience over things and wish for fintechs to be more people-centric. Fintechs often create competitive advantage by being able to tailor offerings for niche markets. Consumers appreciate the personal approach, feel like they’re supporting positive change, and are increasingly looking for companies that align better with their values. If another financial institution does this in a better way, they won’t hesitate to switch providers. ... We know what makes a ‘good’ fintech, but a fintech that is a force for good needs to be reaching wider than the immediate financial communities needs. Fintechs can be innovative in their approaches and therefore have the ability and potential to help people in need. We’re already seeing examples of this where fintechs have encouraged financial inclusion,
SIKE was among several algorithms that passed a NIST competition to identify and define standardized post-quantum algorithms. Because quantum computers represent a threat to current measures for securing information and data, the organization wanted to pinpoint algorithms that stood the best chance of withstanding attacks from quantum computers. In a blog post, Steven Galbraith, a University of Auckland mathematics professor and a leading cryptographic expert, explains how they accomplished the hack: “The attack exploits the fact that SIDH has auxiliary points and that the degree of the secret isogeny is known. The auxiliary points in SIDH have always been an annoyance and a potential weakness, and they have been exploited for fault attacks, the GPST adaptive attack, torsion point attacks, etc.” It’s not the end for SIKE. There may be ways to modify the algorithm to withstand these specific types of attacks. However, in an Ars Technica story, Jonathan Katz, professor in the department of computer science at the University of Maryland, said the news that a classical computer could crack an encryption scheme meant to be safe from quantum devices is troubling.
领英推荐
One of the most efficient ways of eliminating configuration drift is adopting infrastructure-as-code principles and using solutions such as Terraform. Instead of manually applying changes to sync the environments, which is inherently an error-prone process, you would define the environments using code. Code is clear, and is applied/run the same on any number of resources, without the risk of omitting something or reversing the order of some operations. By leveraging code versioning (e.g Git), an infrastructure-as-code platform also provides a detailed record, including both present and past configuration, which removes the issue of undocumented modifications and leaves an audit trail as an added bonus. Tools like Terraform, Pulumi, and Ansible are designed for configuration management and can be used to identify and signal drift, sometimes even correcting it automatically—so you get the chance of making things right before they have a real impact on your systems. As with any tool, the outcome depends on how you’re using it. Using a tool like Terraform does not make your company immune to configuration drift by itself.
Quantum computing at scale is expected to revolutionize a range of industries, as it has the potential to be exponentially faster than classical computers at specific applications. Both China and the United States, among others, have already started national initiatives for this new paradigm. Israel launched its own initiative in 2018, for which in February it announced a $62 million budget. Israel is also placing bets on quantum. The Israel Innovation Authority (IIA) has selected Quantum Machines to establish its national Quantum Computing Center. It will host Israel’s first fully functional quantum computers for commercial and research applications. ... According to Quantum Machines, the Center’s computers will have a full-stack software and hardware platform capable of running any algorithm out of the box, including quantum error correction and multi-qubit calibration. As quantum computing is notorious for the various distinct approaches for creating qubits, the platform will also enable multiple qubit technologies, so that the center does not have to bet everything on one technology that perhaps may not turn out to be successful, which reduces the risk.
By releasing the chatbot to the general public, Meta wants to collect feedback on the various problems facing large language models. Users who chat with BlenderBot will be able to flag any suspect responses from the system, and Meta says it’s worked hard to “minimize the bots’ use of vulgar language, slurs, and culturally insensitive comments.” Users will have to opt in to have their data collected, and if so, their conversations and feedback will be stored and later published by Meta to be used by the general AI research community. “We are committed to publicly releasing all the data we collect in the demo in the hopes that we can improve conversational AI,” Kurt Shuster, a research engineer at Meta who helped create BlenderBot 3, told The Verge. ... Crucially, says Mary Williamson, a research engineering manager at Facebook AI Research (FAIR), while Tay was designed to learn in real time from user interactions, BlenderBot is a static model. That means it’s capable of remembering what users say within a conversation?but this data will only be used to improve the system further down the line.