Quote for the day:
"What great leaders have in common is that each truly knows his or her strengths - and can call on the right strength at the right time." -- Tom Rath
Beyond automation: Physical AI ushers in a new era of smart machines
“Physical AI has reached a critical inflection point where technical readiness
aligns with market demand,” said James Davidson, chief artificial intelligence
officer at Teradyne Robotics, a leader in advanced robotics solutions. “The
market dynamics have shifted from skepticism to proof. Early adopters are
reporting tangible efficiency and revenue gains, and we’ve entered what I’d
characterize as the early-majority phase of adoption, where investment scales
dramatically.” ... To train and prepare these models, a new specialized class
of AI model emerged: World Foundation Models. WFMs serve two primary functions
for robotics AI: They enable engineers to develop vast synthetic datasets
rapidly to train robots on unseen actions, and they test these robots in
virtual environments before real-world deployment. WFMs allow developers to
create virtual training grounds that mimic reality through “digital twins” of
environments. Within these simulated scenes, robots learn to navigate
real-world challenges safely and at a pace far exceeding what physical
presence would permit. ... Despite grabbing a lot of headlines, humanoid
robots only represent a small fraction of AI robotics deployments. For now,
it’s collaborative robots, robotic arms and autonomous mobile robots that are
transforming warehouse and factory settings. The forefront example is
Amazon.com Inc., which uses intelligent robots across its warehouses. When Digital Excellence Turns Into Strategic Technical Debt
Asian Paints' digital architecture was built for a world that valued scale,
predictability and discipline. Its systems continuously optimize for
efficiency, minimize variability and ensure consistency across thousands of
dealers and SKUs. For nearly 20 years, these capabilities have directly
contributed to better margins, improved service levels and increased
shareholder confidence. But today's market is different. New entrants, backed
by capital and "largely free from legacy" process constraints, are willing to
accept inefficiencies to gain market share quickly. ... The result is a market
that is more volatile, more tactical, and less patient. Additionally, new
technology plays a vital role in creating a competitive edge. This is where
the strategic technical debt surfaces. Unlike traditional technical debt, this
isn't about outdated systems or underinvestment. ... The difference lies in
architecture and intent. Newer players are born cloud-native, with a more
modular approach, better governance and greater tolerance for experimentation.
They use analytics and AI proactively to adjust incentives quickly, test local
pricing strategies and pivot dealer engagement models in response to demand.
Speed and flexibility matter more than optimization. ... Strategic technical
debt accumulates because CIOs are rewarded for stability, uptime and
optimization. Optionality, speed and the ability to unlearn don't appear on
scorecards. Over time, this imbalance becomes part of the architecture and
results in digital stress.
The Evolution of North Korea – And What To Expect In 2026
What has changed most notably through 2024 and 2025 is the shift away from
“purely external intrusion” towards “abuse of legitimate access,” says
Pontiroli. “Rather than breaking in, North Korean operators increasingly aim
to be hired as remote IT workers inside real companies, gaining steady income,
trusted network access, and the option to pivot into espionage, data theft, or
follow on attacks.” ... The workers claim to be US based with IT experience,
“but in reality, they are North Korean or proxied by North Korean networks,”
he explains. Over time, the threat actors have developed deep expertise in
software engineering, mobile applications, blockchain infrastructure, and
cryptocurrency ecosystems says Tom Hegel, distinguished threat researcher,
SentinelLABS. ... In parallel, cybersecurity researchers have observed related
campaigns with distinct names and tradecraft. A malicious campaign dubbed
Contagious Interview involves threat actors masquerading as recruiters or
employers to lure job seekers, particularly in tech and cryptocurrency
sectors, into fake interviews that deliver malware such as BeaverTail,
InvisibleFerret, and variants such as OtterCookie, says Pontiroli. ... Today,
fake worker schemes remain an “active and growing threat,” says Jack. KnowBe4
offers training to customers to combat this and strengthen their security
culture, he says. Security leaders must assume that the hiring pipeline itself
is part of the attack surface, says Hegel.
Five Attack-Surface Management Trends to Watch in 2026
In 2026, regulators will anchor security and risk leaders’ approaches to exposure strategy. This will mean not only demonstrating due diligence during annual audits, but also demonstrating proof of resilience every day. Exposure management platforms that can map external assets against regulatory expectations; provide real-time compliance dashboards and metrics; and quantify benefits and exposures to boardrooms will become table stakes. ... Attackers see the enterprise as a single, unified attack surface, with each constituent part informing the next priority: cloud workloads, SaaS, subsidiaries, shadow IT, and third-party dependencies. In 2026, savvy security leaders will be adopting that same perspective. Point-in-time, penetration-test-style engagements and bug-bounty programs will give way to organizations that expect full-scope, attacker-centric discovery of digital asset footprints, as well as automated prioritization to cut through the noise. ... In 2026, successful vendor choices will be those that strike a balance between consolidation and integration. Enterprises will demand more flexible integration into existing workflows, including third-party APIs and visibility into SIEM, SOAR, and GRC tools, as well as the ability to support hybrid and multi-cloud environments without friction. Transparency and visibility into roadmap, enterprise-readiness proofs, and customer success will become significant differentiators in a category that has been defined by mergers and acquisitions.Daon outlines five digital identity shifts for 2026
Daon said non-human identities, including agentic AI systems, are expanding
quickly across enterprise networks. It cited independent 2025 studies reporting
roughly 44% year-on-year growth in non-human identities and a rise in
machine-to-human ratios from around 80:1 to 144:1 in some environments. The
prediction for 2026 is that enterprises will treat autonomous and agentic
systems as full participants in the identity lifecycle. These systems would be
registered, authenticated, authorised and monitored under formal policies, with
containment processes defined in case of compromise or misbehaviour. ... Daon
said progress in techniques such as zero-knowledge proofs, federated learning
and sensor attestation now enables biometric checks on personal devices while
reducing movement of raw biometric data. On-device processing can bind
verification to a specific capture environment and lower the risk of replay or
injection. Local storage of biometric templates supports data-minimisation
approaches. The company expects these on-device checks to align with
proof-of-possession flows and hardware-backed sensor attestations. It said
federated learning and zero-knowledge techniques allow systems to validate
claims without sharing underlying biometric templates with servers. ... Daon
expects continued pressure on pre-hire verification because of deepfake
applicants and impersonation. It said the more significant change in 2026 will
come after hiring as employers adopt continuous workforce assurance.Quantum computing made measurable progress toward real-world use in 2025
Fully functional quantum computers remain out of reach, but optimism across the
field is rising. At the Q2B Silicon Valley conference in December, researchers
and executives pointed to a year
marked
by tangible progress – particularly in hardware performance and scaling – and a
growing belief that quantum advantage for real-world problems may be achievable
sooner than expected. "More people are getting access to quantum computers than
ever before, and I have a suspicion that they'll do things with them that we
could never even think of," said Jamie Garcia at IBM. ... Aaronson, long known
for his critical analysis of claims in quantum computing, described the progress
in qubit fidelity and control systems as "spectacular." However, he cautioned
that new algorithms remain essential for converting that hardware performance
into practical value. While technical strides have been impressive, translating
those advances into applications remains difficult. Ryan Babbush of Google
Quantum AI said hardware continues to outpace software in usefulness. ... Dutch
startup QuantWare introduced an architecture aimed at solving one of the
industry's most significant hardware limitations: scaling up without losing
reliability. The company's superconducting quantum processor design targets
10,000 qubits, roughly 100 times more than today's leading devices. QuantWare's
Matt Rijlaarsdam said the first systems of this size could be operational within
2.5 years.Ship Reliable AI: 7 Painfully Practical DevOps Moves
In AI land, “what changed” is anything that teaches or nudges the model:
training data slices, prompt templates, system instructions, retrieval schemas,
embeddings pipelines, tokenizer versions, and the model binary itself. We treat
each as code. Prompts live next to code with unit tests. We commit small
evaluation sets in-repo for quick signals, and keep larger benchmarks in object
storage with content hashes and a manifest. ... Shiny demos hide flaky edges. We
force those edges to show up in CI, where they’re cheap. Our pipeline runs fast
unit tests, a tiny evaluation suite, and a couple of safety checks against
handcrafted adversarial prompts. The goal isn’t to solve safety in CI; it’s to
block footguns. We test the glue code around the model, we lint prompts for
hard-to-diff formatting changes, and we run a 50-example eval that catches
obvious regressions in latency, grounding, and accuracy. ... For AI pods, that
starts with resource quotas and limits. GPU nodes are expensive; “just one more
experiment” can melt the budget by lunch. We set namespace-level quotas for GPU
and memory, and we stop requests that try to sneak past. For egress, we deny
everything and allow only the API endpoints our apps need. When someone tries to
point a staging pod at a random external endpoint “just to test it,” the policy
does the talking.
What support is available for implementing Agentic AI systems
The adoption of Agentic AI systems is reshaping the way organizations implement security measures, particularly for NHIs. Agentic AI—capable of self-directed learning and decision-making—proves advantageous in deploying security protocols that adapt in real-time to evolving threats. By utilizing such technology, organizations can leverage data-driven insights to enhance their NHI management strategies. ... Given the critical role of NHIs in maintaining robust cloud security, organizations need to adopt advanced methodologies that integrate seamlessly with their existing security frameworks. ... Effective NHI management relies heavily on leveraging insights that stem from analyzing large data sets. Organizations that prioritize the use of data analytics in their cybersecurity strategies can efficiently discover, classify, and monitor machine identities and their associated secrets. Advanced analytical tools can help security teams identify patterns and anomalies in system activities, providing early indicators of potential security threats. These insights make it possible to implement more effective security protocols and prevent unauthorized access before it happens. ... The security of an organization is not solely the responsibility of the IT department; it is a shared responsibility across all stakeholders. Building a culture of security awareness is crucial in ensuring that every member of an organization understands the role that NHIs play in cybersecurity.Godspeed curtain twitchers: DPDP and its peers just got ruthless
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Organisations will have to work on privacy very seriously- in everyday business
operations and in every area, Bhambry cautions. They will have to make sure it
pervades product development, processes (From the onset), internal audit,
regular training and the very culture of that company and its employees.
Enterprises will have to focus on individual rights, consent protocols and data
governance.” There is no doubt that data privacy is going to get stronger,
transparent, and comprehensive, affirms Advocate Dr. Bhavna Sharma, Delhi High
Court. Cybercrime Expert and Legal Consultant, Delhi Police and a techno-legal
policy professional. But it is also going to get complex in 2026 as it shifts
from abstract legal principles to a tangible operational mandate with the
notification of the DPDPA Rules, 2025, adds Dr. Sharma ... “India’s DPDPA and
MeitY’s localisation mandates echo a growing consensus that data sovereignty
equals digital sovereignty. Governments are recognising that control over
citizen data is foundational to national security and economic resilience.”
Cheema explains. In an era marked by competition among nations with their own
data systems, state leaders are taking control, Yadav observes. “They are not
willing to allow strategic assets to slip through their fingers. And as a
result, the government calls for ‘localisation’ to trap extra-territorial
storage simply because it has yet to be regulated by authorities in those
countries.
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