Author: IndNewsWire

Upgrading your home’s exterior siding is one of the most effective ways to improve curb appeal, energy efficiency, and long‑term structural protection. Whether you’re building new, replacing old siding, or addressing damage, selecting experienced professionals makes all the difference. If you need reliable siding contractors Sacramento services, working with specialists ensures quality installation and long-lasting results.

Exterior siding plays a key role in shielding your home from rain, wind, sun exposure, and temperature changes. It also contributes to insulation performance, helping lower heating and cooling costs throughout the year. Because of these benefits, many homeowners in Sacramento prioritize siding upgrades as part of regular maintenance or renovation projects.

Why High‑Quality Siding Matters

Good siding does more than just improve appearance — it protects your home’s structure. Old or damaged siding can allow moisture to penetrate walls, leading to rot, mold growth, or reduced energy efficiency. Replacing worn materials with updated siding helps:

• Shield your property from the elements
• Increase thermal efficiency
• Reduce long‑term maintenance needs
• Boost overall home value

When installed correctly by professionals, siding can last for decades and provide lasting performance even under local climate conditions.

Types of Siding Options for Your Home

There are several popular siding materials, each with its own advantages. The right choice depends on your budget, design preferences, and maintenance expectations.

Vinyl Siding

Vinyl is one of the most widely used options due to its affordability and low maintenance. It resists moisture and fading, and comes in a variety of colors and styles to suit different architectural designs.

Fiber Cement Siding

Fiber cement siding offers exceptional durability and weather resistance. It mimics the look of wood without the same level of upkeep and stands up well to moisture, pests, and temperature extremes.

Wood Siding

Wood siding offers natural beauty and a classic look. While it requires more regular maintenance than other options, many homeowners appreciate its timeless aesthetic.

Metal and Composite Siding

For homeowners seeking modern or industrial looks, metal or composite materials offer strong durability and minimal maintenance. They can complement custom home styles and contemporary designs.

How to Choose the Right Siding Contractor

Selecting the right contractor ensures your project runs smoothly and delivers long‑lasting results. Here are some tips for finding the best professionals:

Evaluate Experience and Reputation

Look for contractors with a track record of successful siding projects. Homeowners often rely on reviews, portfolios, and recommendations to gauge craftsmanship and reliability.

Confirm Licensing and Insurance

Proper licensing means the contractor meets local standards, and insurance protects you in case of accidents or property damage during the job.

Request Clear Estimates

A detailed estimate should outline materials, labor, timeline, and warranty information. Comparing multiple bids helps you understand the scope and cost of your project.

Communication and Professionalism

A good siding contractor communicates clearly, answers questions thoroughly, and provides a plan that matches your expectations. Trustworthy professionals also keep work areas clean and resolve issues proactively.

Maintaining Your Siding After Installation

Once your new siding is installed, regular care can help it last even longer:

• Wash siding annually with a mild detergent
• Check seals around windows, doors, and trim
• Inspect for cracks after storms or extreme weather
• Address small repairs early

Routine maintenance keeps the exterior looking fresh and protects against long‑term damage.

Conclusion

Selecting the right siding contractors ensures your home gets expert care, durable materials, and results that stand up to local weather and time. With professional installation, quality products, and proper maintenance, your siding becomes a long‑term asset that enhances appearance, performance, and value.

Los Angeles, CA – HeroCovers, the company behind the world’s most unique and custom-fit vehicle covers, is thrilled to announce an official partnership with the legendary Hot Wheels—the iconic brand known across generations for its boundary-pushing die-cast cars.

Award-winning UK independent school brings its acclaimed academic curriculum, pastoral care and enrichment programme to international families across Europe, the Caribbean and beyond

An exclusive conversation with Snigdha Gaddam on AI-native systems and software evolution

Introduction: When Software Starts Thinking for Itself

Imagine a world where your smartphone doesn’t just follow programmed instructions but actually learns from your behavior, adapting its performance in real-time without needing constant updates from developers. This isn’t science fiction anymore. Independent researcher Snigdha Gaddam has published groundbreaking work making this vision reality, demonstrating how artificial intelligence can be woven into the fabric of software systems rather than bolted on as an afterthought.

Think about the apps you use daily. Most operate on rigid rules: if you click this button, perform that action. But what if software could observe, learn, and improve itself? Gaddam’s research, recently published in the Journal of Information Systems Engineering and Management, introduces AI-native systems—software that doesn’t just use AI tools but thinks with them from the ground up. Her work achieved a remarkable 97% accuracy in predicting optimal system decisions, proving machines can make intelligent choices almost as reliably as humans.

From healthcare platforms adjusting to patient needs, to financial systems detecting fraud patterns, Gaddam’s vision transforms technology development. We sat down with her to understand how this breakthrough will reshape software development across industries.

The Conversation: Rethinking Software from the Ground Up

Q: Most of us use apps every day, but we don’t think about how they’re built. What’s the fundamental difference between traditional software and AI-native systems?

Think of traditional software like a recipe—you follow exact steps. AI-native systems are like experienced chefs who taste as they go, adjust seasonings based on available ingredients, and learn from past meals. These systems observe data, recognize patterns, and evolve their behavior without needing programmers to manually update every rule. We’re moving from rigid instruction-following to genuine learning and adaptation.

Q: Can you give us a real-world example of how this changes things for everyday users?

Consider a hospital monitoring system. Traditional software alerts nurses when heart rates exceed fixed thresholds. But an AI-native system learns each patient’s normal patterns, factoring in medications, activities, and time of day. Instead of generating false alarms overwhelming staff, it intelligently decides when something truly concerning is happening. My research showed that analyzing user behavior and performance metrics together enables systems to make these nuanced decisions with 97% accuracy.

Q: What did your research specifically demonstrate?

I developed a system using a Random Forest classifier—a method that creates multiple decision-making trees and combines their wisdom for smarter conclusions. Testing with variables representing user interactions and system performance revealed both factors are equally critical. The confusion matrix showed very few errors, proving AI-native systems can work reliably in practice, not just theory.

Q: For someone running a business or working in technology, how would adopting AI-native systems change their daily operations?

It fundamentally shifts the maintenance burden. Today, teams constantly push updates to fix issues or add features. With AI-native systems, software updates itself based on what it learns. Customer service chatbots learn from every conversation, improving understanding of nuance and intent. Inventory systems observe sales patterns, seasonal trends, and supplier reliability, optimizing automatically. This frees teams for innovation rather than constant firefighting. However, it introduces new responsibilities ensuring systems learn ethically and remain transparent in decision-making.

Q: What are the biggest challenges in making this vision a reality across industries?

The technical challenge is data drift—over time, real-world patterns change and AI models become less accurate without continuous retraining. We need systems that recognize when they’re outdated and self-update. The deeper challenge is organizational and ethical. We must ensure learning systems don’t perpetuate biases, that decisions can be explained and trusted, especially in healthcare or criminal justice. My research highlighted these gaps—we have the technology, but need stronger frameworks for responsible deployment.

Looking Ahead: A New Era of Intelligent Software

Snigdha Gaddam’s work represents more than incremental improvement in software engineering—it’s a fundamental reimagining of how we build digital systems. By demonstrating AI can be embedded at software’s core rather than layered on top, she’s opening doors to previously impossible applications. From manufacturing floors where machines coordinate autonomously to optimize production, to educational platforms adapting teaching methods in real-time, implications span every modern sector.

The 97% accuracy her research achieved proves we’re ready to trust machines with complex decisions. Yet as Gaddam emphasized, power comes with responsibility. The software engineering community must develop robust continuous learning practices, establish ethical guidelines, and ensure systems remain accountable to humans they serve.

As organizations grapple with digital transformation, Gaddam’s framework offers a roadmap. The future isn’t about writing better code—it’s building systems that learn, adapt, and evolve alongside us. For engineers, business leaders, and anyone depending on technology, understanding AI-native systems isn’t optional; it’s the essential next step in staying relevant.

The world is more connected than ever. Industry reports estimate that over 15 billion Internet of Things (IoT) devices are currently active worldwide — from smart watches and home assistants to hospital monitors and industrial sensors — with projections suggesting the number could exceed 25 billion devices by 2030.

As these networks expand, so do security risks. Cybersecurity analysts report that IoT-related attacks continue to increase each year, often exploiting unsecured or poorly monitored devices.

In a recent study published in the Journal of Information Systems Engineering and Management, Sushma Babburi, an independent researcher based in the United States, proposes a new framework that integrates Blockchain and Artificial Intelligence (AI) to make IoT systems more secure, reliable, and scalable

We spoke with Babburi about her research and why building trust into connected systems is becoming increasingly critical.

Q: For readers who may not be technical, what problem are you trying to solve?

Sushma Babburi:
Today, billions of devices constantly collect and transmit data. That includes medical monitors, shipping trackers, traffic sensors, and industrial equipment.

The challenge is that as these networks grow, ensuring that every device remains trustworthy becomes more complex. If even one device is hacked or begins behaving abnormally, it can affect an entire system.

My research focuses on creating a framework that makes IoT systems secure, transparent, and scalable, so they can expand safely without increasing risk.

Q: Why are current IoT systems vulnerable?

Babburi:
Most IoT systems rely on centralized servers. That means all data flows through one core system. If that central point is compromised, overloaded, or misconfigured, the entire network can be affected.

In addition, many devices are installed and then assumed to be trustworthy indefinitely. But devices can malfunction or be compromised over time. Continuous evaluation is essential.

Q: How does blockchain improve security?

Babburi:
Blockchain functions like a secure digital ledger that records information in a way that cannot easily be altered.

Instead of storing device data in one place, blockchain distributes records across multiple network nodes. This makes the system tamper-resistant and transparent.

For industries where accuracy is critical — such as healthcare or logistics — ensuring that device data cannot be secretly modified is extremely important.

Q: Where does Artificial Intelligence come in?

Babburi:
While blockchain protects the integrity of the data, AI monitors device behavior.

In my framework, AI continuously evaluates how devices perform. It analyzes patterns such as response time, data consistency, and operational behavior.

Rather than assuming devices are permanently safe, the system constantly reassesses them.

Q: You mention “trust scoring.” What does that mean in simple terms?

Babburi:
It’s similar to a credit score — but for connected devices.

Each device receives a dynamic trust score based on how reliably it behaves. If it shows unusual patterns, the score decreases.

This allows the system to flag or isolate potentially compromised devices before they cause broader disruption.

Q: How does your research detect problems early?

Babburi:
The framework includes anomaly detection that identifies unusual behavior in real time.

For example, if a sensor suddenly transmits data outside its normal range, the system can detect that quickly.

Early detection is especially important in sectors like healthcare, industrial automation, and smart city infrastructure, where system reliability directly affects safety.

Q: Blockchain is sometimes criticized for scalability issues. How do you address that?

Babburi:
Scalability is a real concern as IoT networks grow into millions of devices.

The research evaluates transaction processing performance under simulated IoT workloads and explores optimizations such as hybrid consensus mechanisms and edge computing.

The objective is to maintain strong security while ensuring operational efficiency.

Q: Which industries could benefit most from this work?

According to Babburi, the framework is designed to be domain-agnostic and adaptable across industries.

Examples include:

• Healthcare: securing connected medical devices
• Logistics: protecting supply chain data
• Industrial systems: enabling predictive maintenance
• Smart cities: ensuring reliable sensor-driven infrastructure

As IoT adoption accelerates globally, scalable and trustworthy architectures are becoming foundational to digital infrastructure.

Q: What is the broader vision behind your research?

Sushma Babburi:
We are moving toward a world where connected devices influence real-time decisions — from patient monitoring to traffic management.

If those systems are not trustworthy, the consequences can be significant.

By combining decentralized security with intelligent monitoring, we can build IoT ecosystems that are resilient, scalable, and transparent.

That foundation of trust will be critical as digital infrastructure continues to expand.

Author Note

Sushma Babburi is an independent researcher specializing in Blockchain-enabled and AI-driven data systems. Her study, Integrating Blockchain and AI for Trusted and Scalable IoT Data Ecosystems, was published in the Journal of Information Systems Engineering and Management

New compliance mandates, balcony safety deadlines, and a shifting insurance landscape are redefining what buyers need to know before closing on apartment buildings in Southern California.

By Nathan Sewell

Nathan Sewell is the founder of LA Building Inspections & Compliance, a building advisory and compliance firm serving property managers, investors, and owners throughout Los Angeles County. He is ICC-certified in both California Residential and Commercial inspection, with an architecture and building design background.

For decades, buying an apartment building in Los Angeles followed a fairly predictable due diligence process. Hire an inspector. Get a report on the roof, the plumbing, the electrical. Negotiate repairs or a price adjustment. Close. That checklist approach — similar to what sellers might order through a Pre-Listing Inspection before putting a property on the market — is no longer sufficient. A series of new state and county regulations enacted within the past two years have fundamentally changed the risk profile of multifamily real estate in Southern California. Buyers who rely solely on a traditional property inspection are now closing on buildings with compliance liabilities they do not know about, deferred obligations they have not budgeted for, and deadlines that begin counting the moment they take ownership.

The Regulatory Shift

The most significant change is LA County’s Rental Housing Habitability Program (RHHP), which launched in October 2024 and requires all rental units in unincorporated LA County to be inspected for habitability compliance every four years. The program covers an estimated 115,000 rental units. For buyers acquiring properties in unincorporated areas — including large portions of East LA, South LA, the San Gabriel Valley, and the Antelope Valley — this means inheriting either a compliant building or one that is overdue for its mandatory inspection. Properties that fail RHHP inspections and do not correct violations within the required timeframe can be placed into the county’s Rent Escrow Account Program (REAP), where tenants pay rent to a county escrow account instead of to the landlord. Fines compound and legal exposure increases. RHHP is not the only new mandate. California’s SB 721 requires balcony and exterior elevated element inspections for apartment buildings with three or more units, and SB 326 imposes a similar requirement on condominiums and homeowner associations. Buildings that have not been inspected are already past due, meaning new owners inherit that obligation immediately.

What Standard Inspections Miss

A traditional property inspection evaluates the physical condition of a building. It identifies defects, safety concerns, and deferred maintenance. For a multifamily acquisition in today’s regulatory environment, that scope leaves critical gaps. The first gap is compliance status. A standard inspection does not verify whether RHHP inspections are current, whether SB 721 balcony inspections have been completed, or whether the property’s rent stabilization status under the Los Angeles Rent Stabilization Ordinance (RSO) is properly documented. These are regulatory positions that directly affect operating costs and legal exposure. The second gap is permit history. Los Angeles has one of the highest rates of unpermitted work in the country. A converted garage that functions as a rental unit may still be illegal if no permit was ever pulled, exposing the owner to enforcement action, insurance disputes, and potential loss of rental income. The third gap is capital expenditure forecasting. Buyers need to know not just what is broken today, but what will need replacement in three, five, and ten years. Without a CapEx projection, underwriting is based on incomplete information.

The Insurance Factor

Southern California’s insurance market has tightened dramatically in recent years. Carriers are reducing coverage, increasing premiums, and in some cases refusing to renew policies for properties with deferred maintenance or unresolved code issues. Multifamily buyers must now evaluate insurability alongside condition and compliance. Sellers who commission a Pre Listing Inspection before marketing the property are often better positioned, as they can identify insurability or compliance concerns early and address them before they become leverage points during escrow.

What Investor-Grade Due Diligence Looks Like Now

For buyers acquiring multifamily properties in Los Angeles today, due diligence should simultaneously evaluate physical condition, compliance landscape, and financial forecasting. Physical condition includes structural systems, roofing, mechanical, electrical, plumbing, building envelope components, and representative interior unit inspections. Compliance landscape includes RHHP status, SB 721 or SB 326 inspection status, permit history, RSO verification, and local code compliance. Financial forecasting translates inspection findings into a realistic capital expenditure plan, allowing buyers to budget accurately and avoid capital events shortly after closing.

The Cost of Getting It Wrong

The most expensive surprises rarely come from buyers who skip inspections entirely; they come from buyers who rely on inspections that cover only physical condition but ignore compliance. A purchaser may close on a 10-unit property only to discover unresolved RHHP obligations or overdue balcony inspections that require immediate and costly repairs. The information was available before closing. Compliance records are public. Permit histories can be researched. Balcony conditions can be evaluated. The issue is whether the due diligence process was designed for today’s regulatory environment or for one that no longer exists.

What Buyers Should Be Asking

Before hiring an inspector for a multifamily acquisition in Los Angeles, buyers and their advisors should ask whether the scope includes compliance verification in addition to physical condition, whether permit records will be reviewed, whether the report includes capital expenditure projections, whether the inspector holds commercial-level credentials and code knowledge, and whether the final report can serve buyers, lenders, insurance carriers, and property managers alike.

Adapting to the New Landscape

The regulatory environment for rental housing in Los Angeles is unlikely to simplify. Oversight, mandatory inspections, and enforcement mechanisms continue to expand. Investors who understand the compliance landscape and budget accordingly can still acquire strong assets at realistic valuations. But the inspection process that was sufficient five years ago is not sufficient today. The smartest acquisitions are being made by buyers who treat due diligence not as a checkbox, but as a strategic investment in understanding the physical building, the compliance position, and the capital requirements before signing closing documents.

About the Author

Nathan Sewell is the founder of LA Building Inspections & Compliance, a building advisory and compliance firm serving property managers, investors, and owners throughout Los Angeles County and Orange County. He holds ICC certification in both California Residential and Commercial inspection, with additional credentials from ASHI, InterNACHI, and HUD/NSPIRE. His architecture and building design background informs a technical approach to multifamily due diligence, RHHP compliance, and commercial property assessment.

Website: labuildingcompliance.com
Phone: (626) 214-5929
Email: nathan@larentalinspections.com

In a world where data breaches make headlines almost weekly, organizations are under immense pressure to know exactly where their sensitive data lives — and whether it’s protected. That’s where DSPM comes in. If you’ve been hearing this acronym more frequently in cybersecurity conversations, you’re not alone. DSPM is quickly becoming one of the most important concepts in modern data security strategy.

This guide breaks down what DSPM is, how it works, why it matters, and how businesses can use it to stay ahead of increasingly sophisticated threats.

What Is DSPM?

DSPM stands for Data Security Posture Management. At its core, DSPM is a cybersecurity framework that gives organizations continuous visibility into where their sensitive data is stored, who has access to it, how it’s being used, and whether it’s properly secured.

Think of DSPM as a real-time inventory and security audit for your data — across every cloud, database, application, and storage environment you operate in. Rather than relying on periodic manual audits or reactive incident responses, DSPM provides an always-on view of your data security posture.

The term was popularized by Gartner and has gained enormous traction as businesses accelerate their cloud adoption and data sprawl becomes increasingly difficult to manage manually.

Why DSPM Matters Now More Than Ever

Data is no longer confined to a single server room. Modern organizations store data across multi-cloud environments, SaaS platforms, data warehouses, and third-party tools — often without a complete picture of where everything sits or who can access what.

This creates a dangerous blind spot. Security teams may assume their data is protected, but shadow data — copies of sensitive files, misconfigured storage buckets, or forgotten databases — can sit exposed for months before anyone notices. In fact, misconfigurations in cloud environments are among the leading causes of data breaches today.

DSPM directly addresses this problem. By continuously discovering and classifying data, it eliminates the guesswork and gives security teams the clarity they need to act quickly and decisively.

How DSPM Works

DSPM platforms typically operate through a combination of automated discovery, classification, risk analysis, and remediation guidance. Here’s how the process generally unfolds.

Data Discovery is the first step. The DSPM tool scans across your entire data ecosystem — structured databases, unstructured file stores, cloud platforms like AWS, Azure, and Google Cloud, and SaaS applications — to find every instance of sensitive data. This includes data you know about and, critically, data you’ve forgotten about.

Data Classification comes next. Once data is discovered, the platform categorizes it based on sensitivity. Is it personally identifiable information (PII)? Financial records? Intellectual property? Health data? Classification helps security teams prioritize where to focus their efforts.

Risk Assessment ties the data to its security context. The DSPM platform evaluates who has access to each dataset, whether access permissions are appropriate, whether encryption is in place, and whether any compliance policies are being violated. It assigns risk scores to help teams identify the most critical vulnerabilities first.

Remediation and Monitoring is the ongoing phase. Based on risk findings, DSPM tools either auto-remediate issues or provide clear recommendations for security teams to act on. Continuous monitoring ensures that new data — or changes to existing data environments — are caught in real time rather than discovered weeks later during an audit.

Key Benefits of DSPM

Organizations that implement DSPM gain several significant advantages over those relying on traditional data security approaches.

Complete data visibility means security teams always know where sensitive data lives, even as it moves or is copied across environments. This visibility is foundational to any effective data protection strategy.

Reduced risk of breaches follows naturally from that visibility. When you know where your data is and who can access it, you can close security gaps before attackers exploit them.

Faster compliance is another major benefit. Regulations like GDPR, HIPAA, CCPA, and PCI-DSS require organizations to demonstrate control over their sensitive data. DSPM automates much of the evidence collection and posture validation needed for compliance audits, saving significant time and resources.

Proactive rather than reactive security shifts the organizational mindset from responding to breaches to preventing them. DSPM enables this shift by surfacing risks before they become incidents.

DSPM vs. CSPM: What’s the Difference?

A common source of confusion is the distinction between DSPM and CSPM (Cloud Security Posture Management). While they sound similar, they operate at different layers.

CSPM focuses on the security configuration of your cloud infrastructure — things like network settings, identity policies, and resource configurations. DSPM, on the other hand, focuses specifically on the data itself. The two are complementary; many organizations deploy both to get comprehensive coverage of their cloud security posture.

Who Needs DSPM?

Any organization that handles sensitive data at scale — which today includes virtually every mid-to-large enterprise — can benefit from DSPM. It’s particularly critical for companies in heavily regulated industries like healthcare, finance, legal, and retail, where the consequences of a data exposure go beyond reputational damage and into significant legal liability.

As data environments grow more complex and regulatory scrutiny increases, DSPM is shifting from a “nice to have” to an essential component of a mature security program.

Final Thoughts

DSPM gives organizations something they’ve long struggled to achieve: true clarity over their data. In an era defined by cloud complexity, regulatory pressure, and sophisticated cyberattacks, that clarity isn’t just valuable — it’s essential. Whether you’re building out your security stack for the first time or looking to strengthen an existing program, understanding and implementing DSPM is a smart, strategic move.