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In this respect, I believe regulators have fallen short. In a world facing ongoing cyber threats, the standards for cybersecurity are set surprisingly low that their rules typically only recognize encryption of all stored data as a requirement. This is despite the fact that encryption—not firewalls, monitoring, identity management or multifactor authentication—is the purpose-built technology for protecting data against the strongest and most capable adversaries. Stronger regulations are needed to ensure encryption becomes a mandated standard, not just an optional recommendation.

Fortunately, companies need not wait until regulators realize their folly and can opt to do better today. Some companies already have. They approach data security as an exercise in risk mitigation rather than passing an audit. From this perspective, data encryption quickly becomes an obvious requirement for all their sensitive data as soon as it is ingested into a data store.

Another beneficial development is that encryption has become easier and faster to implement, including the ability to process encrypted data without exposure, a capability known as privacy-enhanced computation. While there will always be some overhead to adopting data encryption, many have found that the return on investment has shifted decisively in favor of encrypting all sensitive data due to its substantial security benefits.

While the technology itself is impressive, its true potential lies in how leaders manage its adoption. Fostering a culture of innovation and continuous learning is crucial for success in this new industrial era. Leaders must ensure that their workforce is not only comfortable with automation but is also empowered to collaborate with AI-driven systems. Upskilling and reskilling employees to work alongside AI will create a workforce capable of leveraging technology to enhance operational efficiency.

It’s also essential for business leaders to prioritize cybersecurity and data privacy. The increased connectivity that comes with IIoT introduces new vulnerabilities, and safeguarding company and customer data must be a top priority.

AI, edge computing and IIoT represent a fundamental shift in the way industries operate. The future of manufacturing is not just automated. It is also intelligent, with systems that learn, predict and adapt in real time. For leaders, the challenge is not only implementing these technologies; it’s also fostering an environment of innovation where technology, data and human expertise work together to achieve operational excellence.

“The effects of cyber-enabled crime can be devastating – people losing their life savings, businesses crippled, and trust in digital and financial systems undermined,” INTERPOL Secretary General Valdecy Urquiza said in a statement.

“The borderless nature of cybercrime means international police cooperation is essential, and the success of this operation supported by INTERPOL shows what results can be achieved when countries work together. It’s only through united efforts that we can make the real and digital worlds safer.”

As part of HAECHI-V, INTERPOL said Korean and Beijing authorities jointly dismantled a widespread voice phishing syndicate responsible for financial losses totaling $1.1 billion and affecting over 1,900 victims.

Free ebook #freeisgood — 50th Anniversary Edition ~ Thomas S. Kuhn.

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“One of the most influential books of the 20th century,” the landmark study in the history of science with a new introduction by philosopher Ian Hacking (Guardian, UK).First published in 1962, Thomas Kuhn’s The Structure of Scientific Revolutions” reshaped our understanding of the scientific enterprise and human inquiry in general.” In it, he challenged long-standing assumptions about scientific progress, arguing that transformative ideas don’t arise from the gradual process of experimentation and data accumulation, but instead occur outside of “normal science.” Though Kuhn was writing when physics ruled the sciences, his ideas on how scientific revolutions bring order to the anomalies that amass over time in research experiments are still instructive in today’s biotech age (Science).

While LLMs are trained on massive, diverse datasets, SLMs concentrate on domain-specific data. In such cases, the data is often from within the enterprise. This makes SLMs tailored to industries or use cases, thereby ensuring both relevance and privacy.

As AI technologies expand, so do concerns about cybersecurity and ethics. The rise of unsanctioned and unmanaged AI applications within organisations, also referred to as ‘Shadow AI’, poses challenges for security leaders in safeguarding against potential vulnerabilities.

Predictions for 2025 suggest that AI will become mainstream, speeding up the adoption of cloud-based solutions across industries. This shift is expected to bring significant operational benefits, including improved risk assessment and enhanced decision-making capabilities.