Daily Tech Digest - December 10, 2023

'Move Fast And Break Things' Doesn’t Apply To AI

Given the urgency around generative AI, those looking for a first-mover advantage or those fearing being left behind may be tempted to adopt the "move fast and break things" mantra. After all, it has long been a staple of Silicon Valley culture. But following it would be a mistake in this instance. ... Consider the analogy of building a house—you wouldn’t just start digging immediately. You need to lay the groundwork first. You need to be planning, consulting structural engineers, involving site visitors, commissioning architectural drawings and building control. It is all essential work that needs to be completed before a brick is laid. But once it has been, confidence in the build skyrockets because there is a clear procedure to follow. Going slower to go faster also applies to AI. Developing a strategy for AI requires deep expertise and a first-class analysis of organizational data. This involves getting a holistic view of the data within an organization, understanding which elements could have inherent bias and lead to the wrong insights and building a picture of the level of automation that could improve operational efficiency.

Generative AI as a copilot for finance and other sectors

While advanced AI technologies such as quantum computing and blockchain have long been a part of Moody's Analytics' IT arsenal, generative AI has spun off many complex models. That can be challenging for a company with large data sets that is concerned about data privacy and security, said Caroline Casey, general manager for customer experience and innovation at the company, in an interview. Before releasing its Research Assistant product on Dec. 4, Moody's created an internal copilot product -- not to be confused with Microsoft Copilot. Research Assistant is a search and analytical tool built on Azure OpenAI and uses OpenAI's GPT-4. "We know that the purpose of this is not to replace a human," Casey said. "It's to take out the kind of mundane work -- the trying to find information, the retrieval, the searching -- and actually help them to focus on where they've got the best expertise." Moody's began its journey in the summer after the CEO encouraged all employees of Moody's Corp. to be innovators. 

World’s First Cybersecurity & AI Guidelines: Experts Weigh in

Speaking to Techopedia, Nic Chavez, Field Chief Information Officer at DataStax, noted that one of the important takeaways is the cautious and collaborative approach employed by the UK to develop the guideline. “I think it’s important to recognize the caution and collaboration with which NCSC approached this endeavor. By seeking feedback from the international community, including other NATO nations, NCSC was able to triangulate recommendations that were reasonable, swiftly actionable and strong.” In his reaction, Jeff Schwartzentruber, Senior Machine Learning Scientist at eSentire and Industry Research Fellow at Toronto Metropolitan University, told Techopedia that releasing these AI guidelines is a step in the right direction as it will help to expand international cooperation and accelerate commitments on the regulation and appropriate use of AI technologies. “I see this as a positive step forward in terms of expanding the international cooperation and discourse on the regulation and appropriate use of AI technologies. ...”

How the blockchain industry can adopt cybersecurity

While the theoretical underpinnings of blockchain offer unparalleled security benefits, the practical implementation introduces potential vulnerabilities. One such vulnerability lies in the exchange of data between blocks, where cybercriminals can intercept and manipulate information. To fortify blockchain systems against such attacks, the adoption of advanced encryption measures becomes paramount. Just as Distributed Denial of Service (DDoS) attacks are thwarted in traditional systems, blockchain must implement robust encryption to safeguard data exchange between blocks. Another challenge in blockchain security arises from censorship attacks, where malicious validators intentionally disrupt or halt the blockchain protocol. Additionally, attackers may masquerade as validators, gaining trust within the system and executing Trojan attacks. To address these threats, it is essential to employ traditional cybersecurity strategies, including encryption, key management, and DNS hygiene. By integrating artificial intelligence (AI) into the system, organizations can enhance their ability to detect consensus attacks, particularly in Proof of Stake (PoS) validation methods.

SLAM Attack: New Spectre-based Vulnerability Impacts Intel, AMD, and Arm CPUs

The attack is an end-to-end exploit for Spectre based on a new feature in Intel CPUs called Linear Address Masking (LAM) as well as its analogous counterparts from AMD (called Upper Address Ignore or UAI) and Arm (called Top Byte Ignore or TBI). "SLAM exploits unmasked gadgets to let a userland process leak arbitrary ASCII kernel data," VUSec researchers said, adding it could be leveraged to leak the root password hash within minutes from kernel memory. While LAM is presented as a security feature, the study found that it ironically degrades security and "dramatically" increases the Spectre attack surface, resulting in a transient execution attack, which exploits speculative execution to extract sensitive data via a cache covert channel. ... AMD has also pointed to current Spectre v2 mitigations to address the SLAM exploit. Intel, on the other hand, intends to provide software guidance prior to the future release of Intel processors that support LAM. In the interim, Linux maintainers have developed patches to disable LAM by default. 

Taking a strategic view of telecom networks in Indo-Pacific

The Indo-Pacific is home to some of the world’s fastest-growing digital economies harnessing technology for national governance and economic development. Telecommunications connectivity – the internet and mobile penetration base – forms the backbone for these economies. Unsurprisingly, the telecom market in the region is witnessing an upgrade. By 2030, telecom companies are expected to invest US$259 billion in the development of networks in the region. These investments will foster the expansion of the digital economy and act as catalysts for innovation, growth and prosperity, with 5G playing an indispensable role in this. 5G represents a generational shift in wireless telecommunications – anchored on higher data transfer speed and ultra-low latency. It holds the promise of revolutionising how people communicate and consume content on the internet and transforming edtech, telemedicine, precision agriculture, and the Internet of Things. However, 5G technology is not cheap, and developing economies have faced budgetary constraints in deploying it.

How to stop digital twins from being used against you

Beyond device optimization and prolonged lifecycles, however, there’s a dark side of digital twins that warrants careful consideration and mitigation strategies. First and foremost, digital twins offer hackers another chance at sensitive company information, particularly when the device data is stored in plain text in the cloud. Providing these models with up-to-date data means providing sensitive information. This goes beyond mere device information, it can sometimes include the personally identifiable data of employees and customers. Meanwhile, the use of international servers to run digital twin operations further complicates things. Different jurisdictions count different privacy requirements, meaning that cross-border data exchanges to run these simulations can bring regulatory and compliance headaches. Additionally, the connected devices themselves can cause security issues. For example, IoT sensors sometimes operate on outdated and vulnerable operating systems. Additionally, cheap devices are well-known for default credentials and unencrypted communications, an important concern as more than two billion devices come online next year. 

The Role of Non-Executive Directors in Driving Innovation

The agile nature of startups grants them an advantage in driving disruptive innovation. They have a greater appetite for risk and tend to be nimbler than their established counterparts. Free from the shackles of middle management’s confining layers and quarterly reporting pressures, these small entities are often seen as the leaders of innovation. On the other side of the spectrum, large companies, despite having the funds to finance innovation, tend to exhibit risk avoidance to protect individual reputations and the status quo. But the acquisition of innovative companies can be a strategic move for larger corporations, provided the innovative culture of the smaller entity is preserved in the process. ... NEDs play an important role in balancing the need for funding innovation against potential impacts on existing business practices. But conflict often emerges between securing immediate profits for shareholders and investing in long-term growth fueled by innovation. However, there is evidence that companies built for the future—those that prioritize innovation—can generate shareholder returns almost three times greater than those of the broader market reflected in the S&P 1200.

Surviving The Polycrisis Of Technological Singularity

First, let us agree on what a technological singularity would look like. It is an idea that puts us in an era where predictability ceases to exist and the conventional understanding of technological evolution is of little use. Historically, we as a society have failed to predict the effects of technological evolutions. Humans have usually underestimated the effects of technological disruptions in the long term. The fusion of various revolutionary technologies in this era, such as quantum computing, nanotechnology, superconductivity and AI, will surely propel us into a zone of immense possibilities and daunting uncertainties that are hard to grasp, let alone predict. One could argue that, if we have this stage today, then we are in the nascent stages of technological singularity. The open letter that was written by leaders from various areas of society calling for a pause in AI development for six months is, to me, one clear signal of the beginning of technological singularity. We can slow down its pace, but we may not be able to stop it. At the core of this discussion lies these profound questions: Can humanity harness the potential of these technologies and mitigate the corresponding risks simultaneously?

DevOps Strategies for Connected Car Development

The connected car is a complex ecosystem of software systems. These vehicles have numerous systems that communicate with each other, the driver and the outside world. Managing the development of these systems can be a daunting task, and this is where DevOps strategies come in. DevOps aims to shorten the system development life cycle and provide continuous delivery with high software quality. This methodology is particularly suited to the complex software systems of connected cars, as it encourages a holistic view of the development process, ensuring that all components work together seamlessly. Moreover, DevOps helps to manage the complexity of car software systems by automating tasks, reducing errors and improving efficiency. The use of automated tools for configuration management, deployment and monitoring means less manual work, fewer mistakes, and quicker problem resolution. One of the greatest challenges in connected car development is the need for speed. In this fast-paced industry, companies are under pressure to develop and deploy new features quickly to stay competitive. 

Quote for the day:

"If you genuinely want something, don't wait for it--teach yourself to be impatient." -- Gurbaksh Chahal

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