#critical infrastructure

[gwydionmisha]

China’s cyber army is invading critical U.S. services

[trendynewsnow]

Deliberate Damage to Undersea Cables Raises Alarm in Europe

Deliberate Damage to Undersea Cables: A Growing Concern German Defence Minister Boris Pistorius has confirmed that the damage inflicted on two underwater data transmission cables connecting Germany and Finland was not accidental. “No one believes that these cables were severed by chance,” Pistorius remarked during a meeting of EU defence ministers held in Brussels. He emphasized the seriousness…

[jcmarchi]

David Maher, CTO of Intertrust – Interview Series

New Post has been published on https://thedigitalinsider.com/david-maher-cto-of-intertrust-interview-series/

David Maher, CTO of Intertrust – Interview Series

David Maher serves as Intertrust’s Executive Vice President and Chief Technology Officer. With over 30 years of experience in trusted distributed systems, secure systems, and risk management Dave has led R&D efforts and held key leadership positions across the company’s subsidiaries. He was past president of Seacert Corporation, a Certificate Authority for digital media and IoT, and President of whiteCryption Corporation, a developer of systems for software self-defense. He also served as co-chairman of the Marlin Trust Management Organization (MTMO), which oversees the world’s only independent digital rights management ecosystem.

Intertrust developed innovations enabling distributed operating systems to secure and govern data and computations over open networks, resulting in a foundational patent on trusted distributed computing.

Originally rooted in research, Intertrust has evolved into a product-focused company offering trusted computing services that unify device and data operations, particularly for IoT and AI. Its markets include media distribution, device identity/authentication, digital energy management, analytics, and cloud storage security.

How can we close the AI trust gap and address the public’s growing concerns about AI safety and reliability?

Transparency is the most important quality that I believe will help address the growing concerns about AI. Transparency includes features that help both consumers and technologists understand what AI mechanisms are part of systems we interact with, what kind of pedigree they have: how an AI model is trained, what guardrails exist, what policies were applied in the model development, and what other assurances exist for a given mechanism’s safety and security.  With greater transparency, we will be able to address real risks and issues and not be distracted as much by irrational fears and conjectures.

What role does metadata authentication play in ensuring the trustworthiness of AI outputs?

Metadata authentication helps increase our confidence that assurances about an AI model or other mechanism are reliable. An AI model card is an example of a collection of metadata that can assist in evaluating the use of an AI mechanism (model, agent, etc.) for a specific purpose. We need to establish standards for clarity and completeness for model cards with standards for quantitative measurements and authenticated assertions about performance, bias, properties of training data, etc.

How can organizations mitigate the risk of AI bias and hallucinations in large language models (LLMs)?

Red teaming is a general approach to addressing these and other risks during the development and pre-release of models. Originally used to evaluate secure systems, the approach is now becoming standard for AI-based systems. It is a systems approach to risk management that can and should include the entire life cycle of a system from initial development to field deployment, covering the entire development supply chain. Especially critical is the classification and authentication of the training data used for a model.

What steps can companies take to create transparency in AI systems and reduce the risks associated with the “black box” problem?

Understand how the company is going to use the model and what kinds of liabilities it may have in deployment, whether for internal use or use by customers, either directly or indirectly. Then, understand what I call the pedigrees of the AI mechanisms to be deployed, including assertions on a model card, results of red-team trials, differential analysis on the company’s specific use, what has been formally evaluated, and what have been other people’s experience. Internal testing using a comprehensive test plan in a realistic environment is absolutely required. Best practices are evolving in this nascent area, so it is important to keep up.

How can AI systems be designed with ethical guidelines in mind, and what are the challenges in achieving this across different industries?

This is an area of research, and many claim that the notion of ethics and the current versions of AI are incongruous since ethics are conceptually based, and AI mechanisms are mostly data-driven. For example, simple rules that humans understand, like “don’t cheat,” are difficult to ensure. However, careful analysis of interactions and conflicts of goals in goal-based learning, exclusion of sketchy data and disinformation, and building in rules that require the use of output filters that enforce guardrails and test for violations of ethical principles such as advocating or sympathizing with the use of violence in output content should be considered. Similarly, rigorous testing for bias can help align a model more with ethical principles. Again, much of this can be conceptual, so care must be given to test the effects of a given approach since the AI mechanism will not “understand” instructions the way humans do.

What are the key risks and challenges that AI faces in the future, especially as it integrates more with IoT systems?

We want to use AI to automate systems that optimize critical infrastructure processes. For example, we know that we can optimize energy distribution and use using virtual power plants, which coordinate thousands of elements of energy production, storage, and use. This is only practical with massive automation and the use of AI to aid in minute decision-making. Systems will include agents with conflicting optimization objectives (say, for the benefit of the consumer vs the supplier). AI safety and security will be critical in the widescale deployment of such systems.

What type of infrastructure is needed to securely identify and authenticate entities in AI systems?

We will require a robust and efficient infrastructure whereby entities involved in evaluating all aspects of AI systems and their deployment can publish authoritative and authentic claims about AI systems, their pedigree, available training data, the provenance of sensor data, security affecting incidents and events, etc. That infrastructure will also need to make it efficient to verify claims and assertions by users of systems that include AI mechanisms and by elements within automated systems that make decisions based on outputs from AI models and optimizers.

Could you share with us some insights into what you are working on at Intertrust and how it factors into what we have discussed?

We research and design technology that can provide the kind of trust management infrastructure that is required in the previous question. We are specifically addressing issues of scale, latency, security and interoperability that arise in IoT systems that include AI components.

How does Intertrust’s PKI (Public Key Infrastructure) service secure IoT devices, and what makes it scalable for large-scale deployments?

Our PKI was designed specifically for trust management for systems that include the governance of devices and digital content. We have deployed billions of cryptographic keys and certificates that assure compliance. Our current research addresses the scale and assurances that massive industrial automation and critical worldwide infrastructure require, including best practices for “zero-trust” deployments and device and data authentication that can accommodate trillions of sensors and event generators.

What motivated you to join NIST’s AI initiatives, and how does your involvement contribute to developing trustworthy and safe AI standards?

NIST has tremendous experience and success in developing standards and best practices in secure systems. As a Principal Investigator for the US AISIC from Intertrust, I can advocate for important standards and best practices in developing trust management systems that include AI mechanisms. From past experience, I particularly appreciate the approach that NIST takes to promote creativity, progress, and industrial cooperation while helping to formulate and promulgate important technical standards that promote interoperability. These standards can spur the adoption of beneficial technologies while addressing the kinds of risks that society faces.

Thank you for the great interview, readers who wish to learn more should visit Intertrust.

[code-of-conflict]

AI, Cybersecurity, and National Sovereignty

Introduction: The Role of AI in Cybersecurity

As artificial intelligence (AI) becomes integral to national security, cyber threats increasingly exploit AI-driven vulnerabilities. Both India and China face the challenge of securing their cyber infrastructure while mitigating espionage and offensive cyber operations. The risks include large-scale data breaches, intellectual property theft, and attacks on critical infrastructure. With AI enhancing the scope and speed of cyberattacks, national sovereignty is increasingly threatened by cyber vulnerabilities that transcend borders.

AI-Driven Cyber Threats and Espionage

China has heavily integrated AI into its cyber capabilities, using it to enhance espionage, cyber warfare, and information manipulation. AI-enabled cyber operations allow China to gather vast amounts of intelligence data through advanced hacking techniques. These tools are often deployed through state-sponsored groups, exploiting zero-day vulnerabilities and penetrating government and corporate networks worldwide​.

For example, in 2021, China was accused of orchestrating a large-scale cyber-attack targeting Microsoft Exchange servers, affecting over 30,000 organizations globally. This attack was designed to facilitate espionage, capturing sensitive information ranging from corporate intellectual property to government data​. China's cyber operations underscore the increasing use of AI in orchestrating sophisticated, large-scale intrusions that threaten national sovereignty.

India, while lagging behind China in offensive cyber capabilities, faces persistent cyber espionage threats from Chinese state-sponsored actors. The most notable incidents occurred during the 2020 India-China border standoff, where Chinese hackers targeted India's critical infrastructure, including power grids and government networks​. These attacks highlight the vulnerabilities in India's cybersecurity architecture and its need to enhance AI-driven defenses.

Vulnerabilities and National Sovereignty

AI-driven cyber threats pose significant risks to national sovereignty. For India, the challenges are magnified by the relatively underdeveloped nature of its cybersecurity infrastructure. Although the establishment of the Defence Cyber Agency in 2018 marked a step forward, India still lacks the offensive cyber capabilities and AI sophistication of China​. India's defensive posture primarily focuses on securing critical infrastructure and mitigating cyber intrusions, but it remains vulnerable to cyber espionage and attacks on its digital economy.

China's integration of AI into both military and civilian cyber systems, through its Military-Civil Fusion policy, has bolstered its ability to conduct large-scale cyber operations with deniability. This fusion allows China to leverage private sector innovations for military purposes, making it a formidable cyber power in the Indo-Pacific region​.

Case Studies: Cyber Confrontations

In 2019, a significant cyberattack targeted India's Kudankulam Nuclear Power Plant, which was traced back to North Korea, but was believed to be part of a broader effort involving Chinese actors. This incident highlighted the potential for AI-enhanced malware to target critical infrastructure, posing severe risks to national security.

Similarly, the 2020 Mumbai blackout, reportedly linked to Chinese hackers, emphasized how AI-driven cyberattacks can disrupt essential services, creating chaos in times of geopolitical tension​. These incidents illustrate how AI-driven cyber capabilities are increasingly weaponized, posing severe risks to India's sovereignty and its ability to protect critical infrastructure.

Implications for Future Conflicts

As AI continues to evolve, the cyber domain will become a primary battleground in future conflicts between India and China. AI-enhanced cyber operations provide both nations with the ability to conduct espionage, sabotage, and information warfare remotely, without direct military engagement. For China, these tools are integral to its broader geopolitical strategy, while India must develop its AI and cybersecurity capabilities to protect its national sovereignty and counteract cyber threats​.

Conclusion

The integration of AI into cybersecurity poses both opportunities and challenges for India and China. While China has aggressively developed AI-driven cyber capabilities, India faces an urgent need to enhance its defenses and develop its offensive cyber tools. As cyberattacks become more sophisticated, driven by AI, both nations will continue to grapple with the implications of these developments on national sovereignty and global security.

[onetechavenue]

The Median Recovery Costs for 2 Critical Infrastructure Sectors, Energy and Water, Quadruples to $3 Million in 1 Year, Sophos Survey Finds

Sophos, a global leader of innovative security solutions for defeating cyberattacks, recently released a sector survey report, “The State of Ransomware in Critical Infrastructure 2024,” which revealed that the median recovery costs for two critical infrastructure sectors, Energy and Water, quadrupled to $3 million over the past year. This is four times higher than the global cross-sector median.…

[ohmyfivedotcom]

When Cyber Attacks Are the Least of Our Worries: 5 Shocking Threats to Critical Infrastructure

Introduction paragraph explaining the significance of the list. Use key phrases related to the topic for SEO optimization. Imagine a world where the things we rely on every day suddenly vanish. No power, no water, no internet—sounds like a bad sci-fi movie, right? But it’s more real than you might think. The importance of critical infrastructure can’t be overstated. These systems are the backbone…

[gauricmi]

Safeguarding Our Nation: The Imperative of Critical Infrastructure Protection

In an interconnected world where technology reigns supreme, the protection of our critical infrastructure is paramount. Critical infrastructure forms the backbone of our society, encompassing systems and assets vital for national security, economic stability, and public health and safety. From power grids to transportation networks, water supplies to telecommunications, each component plays a crucial role in sustaining our way of life. Thus, the concept of Critical Infrastructure Protection (CIP) emerges as a cornerstone in ensuring the resilience and security of our nation.

At its core, Critical Infrastructure Protection (CIP) entails the proactive measures taken to safeguard essential assets and systems against a myriad of threats. These threats encompass a broad spectrum, ranging from natural disasters and cyberattacks to physical sabotage and terrorism. The interconnected nature of modern infrastructure magnifies the potential impact of such threats, underscoring the need for comprehensive and robust protection strategies. By prioritizing CIP efforts, we aim to mitigate vulnerabilities, enhance resilience, and minimize the cascading effects of disruptions across critical sectors.

One of the fundamental challenges in Critical Infrastructure Protection lies in the recognition of interdependencies among various infrastructure sectors. A disruption in one sector can often trigger ripple effects, causing widespread consequences across interconnected systems. For instance, a cyberattack targeting financial institutions can disrupt not only the banking sector but also impact transportation, energy, and communication networks. Therefore, a holistic approach to CIP is essential, encompassing cross-sector collaboration, information sharing, and risk management practices.

Get More Insights On This Topic: Critical Infrastructure Protection

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[pebblemaninoff]

thinking about critical infrastructures today. oh boy

[npi]

Multiple bridges on the Columbia River are vulnerable to ship strike, New York Times story notes

For the opening of our story here on The Cascadia Advocate about the collapse of the Francis Scott Key Bridge in Baltimore last week, I suggested that readers contemplate what would happen if there were a similar disaster on the maritime border between Washington and Oregon, writing: “Imagine if one of the vitally important bridges linking Washington and Oregon was hit by a big cargo ship and…

[little-p-eng-engineering]

Little P.Eng.'s Comprehensive Seismic Structural Services Aligned with ASCE 7-22 and NBCC Standards

In an era where architectural ambition pushes the limits of engineering, safeguarding structural integrity against natural calamities, particularly seismic activities, becomes paramount. This detailed exposé delves into the sophisticated seismic structural engineering services provided by Little P.Eng., a firm renowned for its compliance with the latest American Society of Civil Engineers (ASCE) 7-22 standards and the Canadian National Building Code (NBCC). Their work spans across Canada and the United States, encompassing a diverse range of buildings and non-structural elements, reflecting the pinnacle of safety, reliability, and innovation in modern construction.

1. Introduction

The unpredictable nature of seismic activities has long posed a significant challenge to the realms of construction and civil engineering. Within this volatile environment, Little P.Eng. has emerged as a beacon of reliability, offering cutting-edge seismic structural engineering services across Canada and the United States. Their adherence to the ASCE 7-22 and NBCC codes ensures not only the structural integrity of vast construction undertakings but also the safety and longevity of non-structural elements, affirming their position at the forefront of seismic resilience in contemporary infrastructure.

2. Understanding Seismic Structural Engineering

2.1. The Science of Earthquake Engineering

Before delving into Little P.Eng.'s specialized services, one must understand the core principles of seismic structural engineering. This discipline focuses on making buildings and non-structural components resistant to earthquake shocks through specialized planning, design, detailing, and, subsequently, construction. It encompasses geological science, material engineering, and structural analysis to develop structures capable of withstanding seismic disturbances.

2.2. Evolution of Seismic Codes: From ASCE 7-10 to ASCE 7-22

Seismic building codes are dynamic, evolving in response to the continuous advancements in engineering research and catastrophic lessons learned from each seismic event. The transition from ASCE 7-10 to ASCE 7-22 is a reflection of this evolution, marking significant strides in risk reduction and structural robustness, emphasizing not just human safety but also post-earthquake functionality and rapid recovery for communities.

3. Little P.Eng.’s Integration of ASCE 7-22 in Seismic Structural Engineering

3.1. Innovations in Seismic Design Philosophies

Little P.Eng. employs a forward-thinking approach to integrate the innovations outlined in ASCE 7-22. These include state-of-the-art seismic design philosophies involving base isolation, energy dissipation devices, and performance-based seismic design (PBSD), allowing for structures that are more flexible, absorb and dissipate seismic energy, and maintain structural integrity during earthquakes.

3.2. Site-Specific Hazard Analysis and Geotechnical Considerations

One of the critical aspects of ASCE 7-22 is the emphasis on site-specific hazard analyses. Little P.Eng.'s engineers led by Meena Rezkallah carry out comprehensive geotechnical evaluations, considering soil-structure interaction, liquefaction potential, and site-specific seismic hazard assessments. By understanding the geological variances across different regions in North America, they ensure that each design is intrinsically aligned with its environmental context.

4. Adherence to NBCC Standards: Expanding Safety Parameters Across Canada

4.1. Bridging Policies between Countries

While their services in the United States predominantly adhere to ASCE standards, Little P.Eng. seamlessly bridges engineering policies between the U.S. and Canada by aligning their practices with the NBCC. This code compliance not only underscores their versatility in handling cross-border projects but also reflects their commitment to upholding the highest safety and professional standards in every geographical locale.

4.2. Understanding NBCC’s Seismic Provisions

The NBCC has distinct seismic provisions, necessitating specialized knowledge and an adaptive engineering approach. Little P.Eng.'s expertise in Canadian seismic codes ensures that structural and non-structural components comply with regional regulations, catering to Canada's unique seismic challenges, especially in high-risk provinces.

5. Comprehensive Services for Buildings and Non-Structural Elements

5.1. Diverse Building Typologies

Little P.Eng.'s portfolio encompasses a variety of buildings, from residential high-rises and expansive commercial complexes to critical facilities like hospitals and emergency response centers. Each building type presents unique challenges, and the firm’s nuanced, context-oriented approach to seismic retrofitting and sustainable design practices sets industry standards.

5.2. Protecting Non-Structural Components

Beyond the buildings themselves, Little P.Eng. extends its engineering prowess to safeguard non-structural elements. These components, often overlooked, can pose significant hazards during seismic events. From architectural elements to mechanical and electrical systems, the firm implements exhaustive strategies to enhance the safety of these components, thereby protecting human life and minimizing economic loss.

6. Future Directions and Continuous Advancements

6.1. Embracing Technological Innovations

As the field of seismic structural engineering advances, Little P.Eng. remains committed to incorporating new technologies, including artificial intelligence and machine learning, for predictive analysis, design optimization, and risk management. Their continual investment in technology positions them as a leader in future-proofing structures against earthquakes.

6.2. Contribution to Global Seismic Safety Standards

Harnessing Advanced Engineering: Little P.Eng.'s Comprehensive Seismic Structural Services Aligned with ASCE 7-22 and CNBCC Standards in North America

7. Conclusion

Little P.Eng.’s comprehensive seismic structural engineering services, grounded in the latest ASCE and NBCC standards, represent a confluence of scientific mastery, innovative engineering, and a deep commitment to safeguarding human lives and investments. Their work across diverse building typologies and non-structural components in Canada and the United States cements their stance as a pivotal player in shaping resilient, sustainable, and safe urban landscapes. As seismic activity remains an unpredictable threat, the foresight and innovation of firms like Little P.Eng. are society's best bet for a safer tomorrow.

References

[1] American Society of Civil Engineers. (2022). Minimum Design Loads and Associated Criteria for Buildings and Other Structures (ASCE/SEI 7-22). ASCE.

[2] National Research Council Canada. (2020). National Building Code of Canada.

Tags:

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Seismic Bracing Experts

Located in Calgary, Alberta; Vancouver, BC; Toronto, Ontario; Edmonton, Alberta; Houston Texas; Torrance, California; El Segundo, CA; Manhattan Beach, CA; Concord, CA; We offer our engineering consultancy services across Canada and United States. Meena Rezkallah.

[yodasec-expose-news]

Unveiling the Latest Updates on the Chinese Cyber Army's Targeting of the Texas Power Grid

Introduction: Understanding the Threat Posed by the Chinese Cyber ArmyChina’s cyber army, including state-sponsored hacking groups affiliated with the People’s Liberation Army (PLA), such as “Volt Typhoon,” has been reported to target critical infrastructure and military installations in various locations, including Guam, Hawaii, and Texas[1]. The Chinese Ministry of State Security-affiliated…

[jcmarchi]

ApertureData Secures $8.25M Seed Funding and Launches ApertureDB Cloud to Revolutionize Multimodal AI

New Post has been published on https://thedigitalinsider.com/aperturedata-secures-8-25m-seed-funding-and-launches-aperturedb-cloud-to-revolutionize-multimodal-ai/

ApertureData Secures $8.25M Seed Funding and Launches ApertureDB Cloud to Revolutionize Multimodal AI

ApertureData, a company at the forefront of multimodal AI data management, has raised $8.25 million in an oversubscribed seed round to drive the development and expansion of its groundbreaking platform, ApertureDB. The round was led by TQ Ventures with participation from Westwave Capital, Interwoven Ventures, and a number of angel investors. The funding will allow ApertureData to scale its operations and launch its new cloud-based service, ApertureDB Cloud, a tool designed to simplify and accelerate the management of multimodal data, which includes images, videos, text, and related metadata.

Addressing the Multimodal Data Crisis

The growth of AI has led to an explosion in the generation of multimodal data across industries such as e-commerce, healthcare, retail, agriculture, and visual inspection. Despite this growth, most organizations struggle to effectively manage and utilize this data.  This inefficiency often hampers AI development, leading to longer project timelines and lower returns on investment.

ApertureData’s flagship product, ApertureDB, addresses this challenge head-on. It provides a unified database platform specifically built for managing large-scale multimodal data, which includes images, videos, documents, and their associated metadata. Unlike traditional databases focused on textual data, ApertureDB integrates graph and vector search capabilities, allowing businesses to streamline their AI workflows and significantly reduce the time spent on data preparation and management.

The Launch of ApertureDB Cloud

ApertureDB Cloud, the company’s new cloud-based platform, extends the power of ApertureDB, making it easier for enterprises to access and deploy their multimodal AI solutions without complex infrastructure setups. Users can now manage vast datasets with just a few clicks, utilizing ApertureDB Cloud’s advanced graph-vector search capabilities and seamless integration with AI applications. The platform offers a unified data layer that centralizes all relevant data types and metadata, providing fast and efficient querying and retrieval, which is crucial for AI development.

With the launch of ApertureDB Cloud, organizations can now try the platform with a risk-free 30-day trial, making it accessible for AI teams looking to streamline their data operations and scale their AI models.

A Game-Changer for AI and Machine Learning Pipelines

ApertureDB is designed to solve some of the biggest bottlenecks in AI development. By unifying multimodal data management, the platform offers several advantages, including:

35x faster dataset creation compared to traditional data integrations, speeding up AI project timelines.

63% reduction in network transfer of large visual data, improving operational efficiency.

Integrated vector similarity search and advanced graph search capabilities for complex data handling.

These features allow organizations to efficiently manage massive datasets, reducing the time spent on manual data preparation from months to just a few days. The platform is already deployed across multiple industries, from retail and e-commerce to biotechnology and generative AI startups. For instance, a major home furnishings retailer is using ApertureDB to manage product images and metadata, optimizing their recommendation systems and customer insights.

In the biotech sector, ApertureDB is helping AI-driven medical imaging and visual inspection applications, providing seamless access to large volumes of multimodal data.

Backed by Leading Investors

The $8.25 million seed round backing ApertureData was led by TQ Ventures, a New York-based venture capital firm focused on software businesses and technology-driven startups. According to Andrew Marks, General Partner at TQ Ventures, ApertureData is uniquely positioned to be a foundational player in the emerging AI landscape:

 “ApertureData has steadily built an amazing business with a wide view on the tech stack. They knew early on that traditional databases, which are geared toward textual data, would be insufficient for managing more complex multimodal data. The quantum of multimodal data and the desire to leverage it for analysis and machine learning is likely to explode over the coming decade as we are already seeing with the growth in use cases for generative and multimodal AI. And so, the work ApertureData is doing today will be foundational towards building the best infrastructure for emerging multimodal AI applications across various industries.”

TQ Ventures, founded in 2018, has a portfolio of over 80 investments and $1 billion under management, giving ApertureData access to a broad network of resources and expertise.

Also participating in the round were Westwave Capital, a pre-seed and seed-stage enterprise investor with a focus on AI, robotics, and analytics, and Interwoven Ventures, a firm specializing in early-stage investments in AI, robotics, and healthcare technology. Both investors bring significant operational experience and industry knowledge to help ApertureData scale and refine its platform for the future of multimodal AI.

Expanding Use Cases for Multimodal Data

ApertureDB’s potential spans a wide range of applications, as industries increasingly generate multimodal data and look for ways to turn this data into actionable insights. The platform’s unique ability to integrate knowledge graphs and multimodal data search functions makes it ideal for AI-driven tasks in e-commerce, agriculture, healthcare, and beyond.

For example, in smart retail, ApertureDB allows retailers to use customer data, images, and metadata to deliver personalized product recommendations and improve the customer experience. In smart agriculture, the platform helps farmers analyze images and geolocation data to optimize farming practices. Medical imaging companies leverage ApertureDB’s ability to handle large multimodal medical datasets, facilitating advanced AI-driven diagnostics.

The Road Ahead for ApertureData

With its newly secured funding, ApertureData plans to scale production deployments, enhance its platform’s user experience, and integrate more ecosystem solutions to cater to various AI and machine learning workflows. The company is also looking to expand its marketing and sales efforts, positioning itself as a leader in multimodal AI data management.

Vishakha Gupta, CEO of ApertureData, envisions a future where the demand for multimodal AI will continue to surge:

“The increasing adoption of multimodal data in powering advanced AI experiences, including multimodal chatbots and computer vision systems, has created a significant market opportunity. As more companies look to leverage multimodality, the demand for efficient management solutions like ApertureDB is expected to grow.”

Co-founded by Vishakha Gupta and Luis Remis, both former researchers at Intel Labs with deep expertise in AI and data infrastructure, ApertureData has grown quickly in response to the needs of the modern AI landscape. Their firsthand experience with managing large datasets of visual data inspired the creation of ApertureDB, a tool that is transforming how companies handle AI and machine learning pipelines.

As enterprises increasingly look to multimodal data to drive AI innovations, ApertureData is poised to lead the charge by providing the critical infrastructure needed to handle the vast, complex datasets of the future. The company’s platform is set to play a vital role in the next generation of AI innovations, helping companies turn data into competitive advantage.

[howdoesone]

How does one prioritize the distribution of vaccines during a pandemic?

Priority Distribution of Vaccines During a Pandemic Introduction During a pandemic, when vaccine supplies are limited, it becomes essential to prioritize the distribution of vaccines to maximize their impact on public health. Determining the order in which different population groups receive vaccines requires careful consideration of various factors, such as vulnerability to the disease, risk of…

[disasterriskreductionday]

Good governance and preparation are key to reducing the vulnerability of critical infrastructure.

Of the 7 #SendaiFramework targets, Target D focuses on reducing disaster damage to critical infrastructure. Here's what that means: