#database cloning automation

[clonetab]

Checkout the clonetab software which help you solutions for oracle database, ERP's & EBS platforms from data disaster recovery, database backup, database cloning automation, quick snapshots and soo....on.

[lazeecomet]

The Story of KLogs: What happens when an Mechanical Engineer codes

Since i no longer work at Wearhouse Automation Startup (WAS for short) and havnt for many years i feel as though i should recount the tale of the most bonkers program i ever wrote, but we need to establish some background

WAS has its HQ very far away from the big customer site and i worked as a Field Service Engineer (FSE) on site. so i learned early on that if a problem needed to be solved fast, WE had to do it. we never got many updates on what was coming down the pipeline for us or what issues were being worked on. this made us very independent

As such, we got good at reading the robot logs ourselves. it took too much time to send the logs off to HQ for analysis and get back what the problem was. we can read. now GETTING the logs is another thing.

the early robots we cut our teeth on used 2.4 gHz wifi to communicate with FSE's so dumping the logs was as simple as pushing a button in a little application and it would spit out a txt file

later on our robots were upgraded to use a 2.4 mHz xbee radio to communicate with us. which was FUCKING SLOW. and log dumping became a much more tedious process. you had to connect, go to logging mode, and then the robot would vomit all the logs in the past 2 min OR the entirety of its memory bank (only 2 options) into a terminal window. you would then save the terminal window and open it in a text editor to read them. it could take up to 5 min to dump the entire log file and if you didnt dump fast enough, the ACK messages from the control server would fill up the logs and erase the error as the memory overwrote itself.

this missing logs problem was a Big Deal for software who now weren't getting every log from every error so a NEW method of saving logs was devised: the robot would just vomit the log data in real time over a DIFFERENT radio and we would save it to a KQL server. Thanks Daddy Microsoft.

now whats KQL you may be asking. why, its Microsofts very own SQL clone! its Kusto Query Language. never mind that the system uses a SQL database for daily operations. lets use this proprietary Microsoft thing because they are paying us

so yay, problem solved. we now never miss the logs. so how do we read them if they are split up line by line in a database? why with a query of course!

select * from tbLogs where RobotUID = [64CharLongString] and timestamp > [UnixTimeCode]

if this makes no sense to you, CONGRATULATIONS! you found the problem with this setup. Most FSE's were BAD at SQL which meant they didnt read logs anymore. If you do understand what the query is, CONGRATULATIONS! you see why this is Very Stupid.

You could not search by robot name. each robot had some arbitrarily assigned 64 character long string as an identifier and the timestamps were not set to local time. so you had run a lookup query to find the right name and do some time zone math to figure out what part of the logs to read. oh yeah and you had to download KQL to view them. so now we had both SQL and KQL on our computers

NOBODY in the field like this.

But Daddy Microsoft comes to the rescue

see we didnt JUST get KQL with part of that deal. we got the entire Microsoft cloud suite. and some people (like me) had been automating emails and stuff with Power Automate

This is Microsoft Power Automate. its Microsoft's version of Scratch but it has hooks into everything Microsoft. SharePoint, Teams, Outlook, Excel, it can integrate with all of it. i had been using it to send an email once a day with a list of all the robots in maintenance.

this gave me an idea

and i checked

and Power Automate had hooks for KQL

KLogs is actually short for Kusto Logs

I did not know how to program in Power Automate but damn it anything is better then writing KQL queries. so i got to work. and about 2 months later i had a BEHEMOTH of a Power Automate program. it lagged the webpage and many times when i tried to edit something my changes wouldn't take and i would have to click in very specific ways to ensure none of my variables were getting nuked. i dont think this was the intended purpose of Power Automate but this is what it did

the KLogger would watch a list of Teams chats and when someone typed "klogs" or pasted a copy of an ERROR mesage, it would spring into action.

it extracted the robot name from the message and timestamp from teams

it would lookup the name in the database to find the 64 long string UID and the location that robot was assigned too

it would reply to the message in teams saying it found a robot name and was getting logs

it would run a KQL query for the database and get the control system logs then export then into a CSV

it would save the CSV with the a .xls extension into a folder in ShairPoint (it would make a new folder for each day and location if it didnt have one already)

it would send ANOTHER message in teams with a LINK to the file in SharePoint

it would then enter a loop and scour the robot logs looking for the keyword ESTOP to find the error. (it did this because Kusto was SLOWER then the xbee radio and had up to a 10 min delay on syncing)

if it found the error, it would adjust its start and end timestamps to capture it and export the robot logs book-ended from the event by ~ 1 min. if it didnt, it would use the timestamp from when it was triggered +/- 5 min

it saved THOSE logs to SharePoint the same way as before

it would send ANOTHER message in teams with a link to the files

it would then check if the error was 1 of 3 very specific type of error with the camera. if it was it extracted the base64 jpg image saved in KQL as a byte array, do the math to convert it, and save that as a jpg in SharePoint (and link it of course)

and then it would terminate. and if it encountered an error anywhere in all of this, i had logic where it would spit back an error message in Teams as plaintext explaining what step failed and the program would close gracefully

I deployed it without asking anyone at one of the sites that was struggling. i just pointed it at their chat and turned it on. it had a bit of a rocky start (spammed chat) but man did the FSE's LOVE IT.

about 6 months later software deployed their answer to reading the logs: a webpage that acted as a nice GUI to the KQL database. much better then an CSV file

it still needed you to scroll though a big drop-down of robot names and enter a timestamp, but i noticed something. all that did was just change part of the URL and refresh the webpage

SO I MADE KLOGS 2 AND HAD IT GENERATE THE URL FOR YOU AND REPLY TO YOUR MESSAGE WITH IT. (it also still did the control server and jpg stuff). Theres a non-zero chance that klogs was still in use long after i left that job

now i dont recommend anyone use power automate like this. its clunky and weird. i had to make a variable called "Carrage Return" which was a blank text box that i pressed enter one time in because it was incapable of understanding /n or generating a new line in any capacity OTHER then this (thanks support forum).

im also sure this probably is giving the actual programmer people anxiety. imagine working at a company and then some rando you've never seen but only heard about as "the FSE whos really good at root causing stuff", in a department that does not do any coding, managed to, in their spare time, build and release and entire workflow piggybacking on your work without any oversight, code review, or permission.....and everyone liked it

[meret118]

This week, we spoke with four federal-government IT professionals—all experienced contractors and civil servants who have built, modified, or maintained the kind of technological infrastructure that Musk’s inexperienced employees at his newly created Department of Government Efficiency are attempting to access. In our conversations, each expert was unequivocal: They are terrified and struggling to articulate the scale of the crisis.

. . .

“This is the largest data breach and the largest IT security breach in our country’s history—at least that’s publicly known,” one contractor who has worked on classified information-security systems at numerous government agencies told us this week. “You can’t un-ring this bell. Once these DOGE guys have access to these data systems, they can ostensibly do with it what they want.”

. . .

Given the scope of what these systems do, key government services might stop working properly, citizens could be harmed, and the damage might be difficult or impossible to undo. As one administrator for a federal agency with deep knowledge about the government’s IT operations told us, “I don’t think the public quite understands the level of danger.”

. . .

These systems are immense, they are complex, and they are critical. A single program run by the FAA to help air-traffic controllers, En Route Automation Modernization, contains nearly 2 million lines of code; an average iPhone app, for comparison, has about 50,000. The Treasury Department disburses trillions of dollars in payments per year.

Many systems and databases in a given agency feed into others, but access to them is restricted. Employees, contractors, civil-service government workers, and political appointees have strict controls on what they can access and limited visibility into the system as a whole. This is by design, as even the most mundane government databases can contain highly sensitive personal information. A security-clearance database such as those used by the Department of Justice or the Bureau of Alcohol, Tobacco, Firearms and Explosives, one contractor told us, could include information about a person’s mental-health or sexual history, as well as disclosures about any information that a foreign government could use to blackmail them.

Even if DOGE has not tapped into these particular databases, TheWashington Post reported on Wednesday that the group has accessed sensitive personnel data at OPM. Mother Jones also reported on Wednesday that an effort may be under way to effectively give Musk control over IT for the entire federal government, broadening his access to these agencies.

. . .

With relatively basic “read only” access, Musk’s people could easily find individuals in databases or clone entire servers and transfer that secure information somewhere else. Even if Musk eventually loses access to these systems—owing to a temporary court order such as the one approved yesterday, say—whatever data he siphons now could be his forever.

With a higher level of access—“write access”—a motivated person may be able to put their own code into the system, potentially without any oversight. The possibilities here are staggering. One could alter the data these systems process, or they could change the way the software operates—without any of the testing that would normally accompany changes to a critical system. Still another level of access, administrator privileges, could grant the broad ability to control a system, including hiding evidence of other alterations. “They could change or manipulate treasury data directly in the database with no way for people to audit or capture it,” one contractor told us. “We’d have very little way to know it even happened.”

. . .

Musk’s efforts represent a dramatic shift in the way the government’s business has traditionally been conducted. Previously, security protocols were so strict that a contractor plugging a non-government-issued computer into an ethernet port in a government agency office was considered a major security violation. Contrast that with DOGE’s incursion. CNN reported yesterday that a 23-year-old former SpaceX intern without a background check was given a basic, low tier of access to Department of Energy IT systems, despite objections from department lawyers and information experts. “That these guys, who may not even have clearances, are just pulling up and plugging in their own servers is madness,” one source told us, referring to an allegation that DOGE had connected its own server at OPM. “It’s really hard to find good analogies for how big of a deal this is.” The simple fact that Musk loyalists are in the building with their own computers is the heart of the problem—and helps explain why activities ostensibly authorized by the president are widely viewed as a catastrophic data breach.

-----

“‘Upgrading’ a system of which you know nothing about is a good way to break it, and breaking air travel is a worst-case scenario with consequences that will ripple out into all aspects of civilian life. It could easily get to a place where you can’t guarantee the safety of flights taking off and landing.” Nevertheless, on Wednesday Musk posted that “the DOGE team will aim to make rapid safety upgrades to the air traffic control system.”

Even if DOGE members are looking to modernize these systems, they may find themselves flummoxed. The government is big and old and complicated. One former official with experience in government IT systems, including at the Treasury, told us that old could mean that the systems were installed in 1962, 1992, or 2012. They might use a combination of software written in different programming languages: a little COBOL in the 1970s, a bit of Java in the 1990s. Knowledge about one system doesn’t give anyone—including Musk’s DOGE workers, some of whom were not even alive for Y2K—the ability to make intricate changes to another.

. . .

Like the FAA employee, the payment-systems expert also fears that the most likely result of DOGE activity on federal systems will be breaking them, especially because of incompetence and lack of proper care. DOGE, he observed, may be prepared to view or hoover up data, but. . . it doesn’t appear to be prepared to carry out savvy and effective alterations to how the system operates.

. . .

But DOGE workers could try anyway. Mainframe computers have a keyboard and display, unlike the cloud-computing servers in data centers. According to the former Treasury IT expert, someone who could get into the room and had credentials for the system could access it and, via the same machine or a networked one, probably also deploy software changes to it. It’s far more likely that they would break, rather than improve, a Treasury disbursement system in so doing, one source told us. “The volume of information they deal with [at the Treasury] is absolutely enormous, well beyond what anyone would deal with at SpaceX,” the source said. Even a small alteration to a part of the system that has to do with the distribution of funds could wreak havoc, preventing those funds from being distributed or distributing them wrongly, for example. “It’s like walking into a nuclear reactor and deciding to handle some plutonium.”

. . .

DOGE is many things—a dismantling of the federal government, a political project to flex power and punish perceived enemies—but it is also the logical end point of a strain of thought that’s become popular in Silicon Valley during the boom times of Big Tech and easy money: that building software and writing code aren’t just dominant skills for the 21st century, but proof of competence in any realm. In a post on X this week, John Shedletsky, a developer and an early employee at the popular gaming platform Roblox, summed up the philosophy nicely: “Silicon Valley built the modern world. Why shouldn’t we run it?”

More at the link.

The coup has already happened, and we lost.

[elsa16744]

Best Practices for Data Lifecycle Management to Enhance Security

Securing all communication and data transfer channels in your business requires thorough planning, skilled cybersecurity professionals, and long-term risk mitigation strategies. Implementing global data safety standards is crucial for protecting clients’ sensitive information. This post outlines the best practices for data lifecycle management to enhance security and ensure smooth operations.

Understanding Data Lifecycle Management

Data Lifecycle Management (DLM) involves the complete process from data source identification to deletion, including streaming, storage, cleansing, sorting, transforming, loading, analytics, visualization, and security. Regular backups, cloud platforms, and process automation are vital to prevent data loss and database inconsistencies.

While some small and medium-sized businesses may host their data on-site, this approach can expose their business intelligence (BI) assets to physical damages, fire hazards, or theft. Therefore, companies looking for scalability and virtualized computing often turn to data governance consulting services to avoid these risks.

Defining Data Governance

Data governance within DLM involves technologies related to employee identification, user rights management, cybersecurity measures, and robust accountability standards. Effective data governance can combat corporate espionage attempts and streamline database modifications and intel sharing.

Examples of data governance include encryption and biometric authorization interfaces. End-to-end encryption makes unauthorized eavesdropping more difficult, while biometric scans such as retina or thumb impressions enhance security. Firewalls also play a critical role in distinguishing legitimate traffic from malicious visitors.

Best Practices in Data Lifecycle Management Security

Two-Factor Authentication (2FA) Cybercriminals frequently target user entry points, database updates, and data transmission channels. Relying solely on passwords leaves your organization vulnerable. Multiple authorization mechanisms, such as 2FA, significantly reduce these risks. 2FA often requires a one-time password (OTP) for any significant changes, adding an extra layer of security. Various 2FA options can confuse unauthorized individuals, enhancing your organization’s resilience against security threats.

Version Control, Changelog, and File History Version control and changelogs are crucial practices adopted by experienced data lifecycle managers. Changelogs list all significant edits and removals in project documentation, while version control groups these changes, marking milestones in a continuous improvement strategy. These tools help detect conflicts and resolve issues quickly, ensuring data integrity. File history, a faster alternative to full-disk cloning, duplicates files and metadata in separate regions to mitigate localized data corruption risks.

Encryption, Virtual Private Networks (VPNs), and Antimalware VPNs protect employees, IT resources, and business communications from online trackers. They enable secure access to core databases and applications, maintaining privacy even on public WiFi networks. Encrypting communication channels and following safety guidelines such as periodic malware scans are essential for cybersecurity. Encouraging stakeholders to use these measures ensures robust protection.

Security Challenges in Data Lifecycle Management

Employee Education Educating employees about the latest cybersecurity implementations is essential for effective DLM. Regular training programs ensure that new hires and experienced executives understand and adopt best practices.

Voluntary Compliance Balancing convenience and security is a common challenge. While employees may complete security training, consistent daily adoption of guidelines is uncertain. Poorly implemented governance systems can frustrate employees, leading to resistance.

Productivity Loss Comprehensive antimalware scans, software upgrades, hardware repairs, and backups can impact productivity. Although cybersecurity is essential, it requires significant computing and human resources. Delays in critical operations may occur if security measures encounter problems.

Talent and Technology Costs Recruiting and developing an in-house cybersecurity team is challenging and expensive. Cutting-edge data protection technologies also come at a high cost. Businesses must optimize costs, possibly through outsourcing DLM tasks or reducing the scope of business intelligence. Efficient compression algorithms and hybrid cloud solutions can help manage storage costs.

Conclusion

The Ponemon Institute found that 67% of organizations are concerned about insider threats. Similar concerns are prevalent worldwide. IBM estimates that the average cost of data breaches will reach 4.2 million USD in 2023. The risks of data loss, unauthorized access, and insecure PII processing are rising. Stakeholders demand compliance with data protection norms and will penalize failures in governance.

Implementing best practices in data lifecycle management, such as end-to-end encryption, version control systems, 2FA, VPNs, antimalware tools, and employee education, can significantly enhance security. Data protection officers and DLM managers can learn from expert guidance, cybersecurity journals, and industry peers’ insights to navigate complex challenges. Adhering to privacy and governance directives offers legal, financial, social, and strategic advantages, boosting long-term resilience against the evolving threats of the information age. Utilizing data governance consulting services can further ensure your company is protected against these threats.

[go2market]

The Role of AI Voice Calls and Personalized AI Videos in Bihar Elections

The power of Artificial Intelligence (AI) and its uses are emerging day by day. AI is now being used in various sectors, from crowd monitoring at the Kumbh Mela to pest detection in agriculture, and even safety systems in railways. Politics is also an interesting sector where AI is being used smartly. AI-powered voice cloning and personalized AI video messages, enhanced with regional language, tone, and advanced lip-syncing, are transforming how leaders connect with voters. In the recent Maharashtra elections, these technologies were deployed to build deep emotional resonance, especially in rural and semi-urban areas.

The Strategic Importance of Bihar

Bihar is not just a large state, it is a political heavyweight. With 40 Lok Sabha seats, its role in shaping the central government is undeniable. Political parties understand that winning Bihar is not just about securing power locally, it has national implications. This strategic significance is pushing parties to explore every possible technological edge to engage, influence, and win voters’ support. Read this detailed article to understand how AI voice calls and AI videos are set to impact political campaigns in Bihar.

How AI is Transforming Political Campaigns in India

1. AI-Generated Voice Calls and Personalized Videos

Political leaders are now using AI voice cloning to create personalized messages that sound exactly like them, in regional dialects. These are delivered as automated voice calls to millions of voters, especially in rural areas where digital access may be limited but mobile penetration is high.

Similarly, AI-generated videos use deepfake technology to lip-sync the leader’s speech into different languages or dialects. This allows parties to connect with diverse linguistic communities without the need for the leader to physically record multiple versions.

2. Hyper-Personalized Messaging

AI algorithms analyze voter data like age, gender, location, voting history, and even social media behavior, to craft personalized messages that resonate with individual concerns. Whether it's an SMS about local infrastructure or a call addressing farmers’ issues, the communication feels directly relevant.

3. Sentiment Analysis and Real-Time Feedback

AI-powered tools scan social media platforms and news outlets to gauge public sentiment around key issues, speeches, or controversies. This helps political strategists adjust their strategy in real time and focus on issues that are gaining traction among the electorate.

CPaaS: The Silent Backbone of Political Communication

Behind the AI dazzle lies a powerful but less visible engine, Communications Platform as a Service (CPaaS). These services enable real-time, scalable communication through SMS, voice, and interactive platforms. Here's how they're playing a key role in Bihar election campaigns

1. Regional Language Bulk SMS

Text messaging remains one of the most effective outreach tools in India, especially in tier-2 and tier-3 cities. Campaigns now use CPaaS platforms to send bulk SMS in regional languages, making the messages more relatable and trustworthy.

2. Automated Voice Calls in Leaders’ Voices

Through a combination of CPaaS and AI voice cloning, parties are sending millions of pre-recorded voice messages in a leader's own voice, delivering emotional, urgent, or motivational appeals that sound personal and authentic to voters.

3. Missed Call Campaigns

This simple but powerful tool allows voters to express support, join a campaign, or access more information, all by just giving a missed call. They're often used to collect databases of supporters, mobilize volunteers, or register new voters.

4. IVR & Toll-Free Numbers for Grievance Redressal

Parties are setting up interactive voice response (IVR) systems and toll-free helplines where voters can register complaints, offer suggestions, or get information. This creates a two-way channel, making voters feel heard and involved in the process.

The Future of AI in Indian Politics

The Bihar elections serve as a testbed for how far AI and communication platforms can be integrated into political strategy. If successful, these tactics will likely become a blueprint for upcoming state and national elections across India.

What’s clear is that we’re entering an era where the battle for the vote is as digital as it is physical. Political communication is becoming faster, smarter, and more personalized, and the voters are at the center of this technological transformation.

Conclusion

In conclusion to this discussion, we can say that the powerful combination of AI and CPaaS technologies is revolutionizing political campaigns in India. In Bihar, this means leaders can “speak” in every dialect, reach every village, and listen to voter complaints all in real-time. Connecting with voters and sharing growth plans for the state is part of all political campaign strategies. When leaders share their growth plans with the citizens, it helps them connect and gain support, that is why voter communication plays a key role in the success of a political campaign. For more information about political campaign services, connect with go2market at 8595080808 or visit us at www.go2market.in

[whycloudserversarethefuture]

Staging on a VPS: Safely Preview Changes Before Going Live

🧪 How to Build a Staging Environment Using Your VPS

Safely test changes before going live — the smart way.

If you're running a website, web app, or SaaS project, you know the pain of broken layouts, buggy features, or downtime after updates. That’s where a staging environment comes in — a replica of your live website where you can test everything before going public.

In this guide, you’ll learn how to set up a reliable staging environment using your VPS hosting (ideal if you're hosted with VCCLHOSTING).

🧠 What Is a Staging Environment?

A staging environment is a testing ground — separate from your production (live) server — that simulates the real-world environment of your website or app. You can use it to:

Test design updates, new features, or plugin installs

Preview major code or content changes

Troubleshoot performance and security

Collaborate with your dev or QA team

Avoid downtime or user experience issues

🛠️ Why Use a VPS for Staging?

Using a VPS (Virtual Private Server) gives you:

Root access for full control

Dedicated resources (RAM, CPU)

Ability to isolate staging from live environment

Freedom to run multiple domains/subdomains or even container-based staging setups

💡 Tip: If you're using VCCLHOSTING, you can easily configure multiple environments on a single VPS or request an additional one at discounted rates for dev/testing purposes.

🧰 Tools You’ll Need

A VPS with Linux (Ubuntu/Debian/CentOS)

Web server: Apache or NGINX

PHP, MySQL/MariaDB stack (or your app’s language/runtime)

Optional: Git, Docker, cPanel, or phpMyAdmin

Domain/subdomain for staging (e.g., staging.yoursite.com)

🔧 Steps to Build a Staging Environment

1. Create a Subdomain or Separate Directory

Subdomain method: Set up staging.yourdomain.com in your DNS settings Point it to a new virtual host directory on your VPS

Folder method: Use a separate folder like /var/www/html/staging

✅ If you use cPanel or DirectAdmin (available on VCCLHOSTING), this can be done with a few clicks.

2. Clone Your Production Site

Manually copy your website files (via SFTP, rsync, or Git)

Export your live database and import it to a new one (e.g., staging_db)

Update configuration files:

Database credentials

Site URL paths (e.g., in WordPress: update wp-config.php and wp_options table)

3. Add Security

You don’t want Google indexing your staging site or hackers testing exploits.

Use .htpasswd to password-protect the staging directory

Block indexing via robots.txt

Restrict IP addresses if needed

Use HTTPS (let's Encrypt SSL or clone your live certificate)

4. Use Version Control (Recommended)

Set up Git to manage your staging deployments:

bashCopy

Edit

git clone https://github.com/yourrepo/project.git

This allows your devs to push to staging for testing before merging to live.

5. Test Your Changes in Staging First

Always use staging to:

Apply plugin/theme updates

Run database migrations

Test performance under simulated load

QA user flows, logins, carts, or contact forms

Once everything works in staging, deploy to live using:

Git-based CI/CD

Manual sync

Hosting control panel tools (e.g., Softaculous staging)

🤖 Bonus: Automate Staging with Docker or Containers

If you manage multiple apps, use Docker Compose or Kubernetes to quickly spin up isolated environments on your VPS.

Example with Docker Compose:

yamlCopy

Edit

version: '3' services: app: image: php:8.1-apache volumes: - ./code:/var/www/html ports: - "8081:80"

🛡️ Staging Environments with VCCLHOSTING

With VCCLHOSTING VPS, you get:

Full root access to configure staging as needed

Support for Linux or Windows environments

Optional cPanel/DirectAdmin for GUI-based staging

Local data center in Kolhapur for low-latency testing

Backup & restore tools to sync between live and staging

🧠 Final Thoughts

A staging environment isn’t just for big companies — it’s for anyone who cares about uptime, stability, and professionalism. Whether you're running a SaaS project or an eCommerce store, setting up staging on your VPS saves time, avoids downtime, and helps you launch with confidence.

🚀 Need Help Setting It Up?

Talk to the team at VCCLHOSTING — we’ll help you set up a staging-ready VPS with backup, SSH, and everything pre-configured.

🔗 www.vcclhosting.com 📞 Call us: 9096664246

[veins09]

How to Build an Instacart Clone App in 5 Easy Steps

I’ve always believed that the on-demand economy isn’t just a trend—it’s a transformation. And if you're anything like me, you've noticed how grocery delivery has gone from a convenience to an expectation. That’s why Instacart clone app development has become such a hot topic among enterprises looking to enter or expand in the online grocery delivery market.

So, whether you're a business unit manager exploring new digital channels or an enterprise leader looking for scalable growth opportunities, let me walk you through how to build an Instacart clone app solution in five simple, strategic steps.

Step 1: Understand the Core Features of Instacart

Before writing a single line of code or hiring a dev team, I always start by breaking down what makes Instacart work so well. Here’s what I look for:

User-friendly interface for quick grocery selection

Real-time inventory updates

Multiple payment gateways

Advanced search and filters

Order tracking & delivery scheduling

Ratings and reviews

Admin dashboard & analytics

This core list becomes the foundation for any Instacart clone app development strategy. I map out which features are must-haves for launch and which ones can be added as part of a future update.

Step 2: Choose the Right Tech Stack

Next, I focus on the technology. A good Instacart clone app solution must be scalable, secure, and responsive. Here's a sample stack I usually recommend:

Frontend: React Native or Flutter (for both iOS and Android)

Backend: Node.js with Express or Django

Database: PostgreSQL or MongoDB

Cloud & Hosting: AWS or Google Cloud

Notifications: Firebase or OneSignal

Payments: Stripe, Razorpay, or PayPal

When choosing a tech stack, I always keep in mind the long-term goals of the business—speed is great, but sustainability is better.

Step 3: Partner with the Right Development Team

This part can’t be rushed. Whether you have an internal IT team or need to hire an external agency, experience with Instacart clone app development is non-negotiable. I look for teams that:

Have a solid portfolio of on-demand apps

Offer UI/UX design, backend development, and post-launch support

Understand third-party integrations (like maps, payment gateways, and CRMs)

If you’re considering a white-label Instacart clone app solution, make sure it's customizable and comes with full source code.

Step 4: Launch with a Localized MVP

Rather than go big right away, I always suggest launching a minimum viable product (MVP) in a specific region. This allows me to:

Test core features with real users

Collect feedback for improvements

Optimize delivery logistics and partnerships

Build local brand awareness

A soft launch helps in shaping the app based on real-world data—not assumptions. It also reduces risk and improves ROI in early phases.

Step 5: Scale with Data and Marketing Automation

After the MVP stage, it's time to scale. I usually focus on:

User acquisition via paid campaigns, SEO, and social media

Loyalty programs to retain repeat users

Analytics dashboards to track KPIs

Marketing automation tools for email, push notifications, and re-engagement

A robust Instacart clone app solution should allow integration with CRMs, marketing tools, and performance analytics. This ensures that as the business grows, the app grows with it.

Final Thoughts

Building an app like Instacart might sound complex at first, but with the right approach and a clear roadmap, it's completely doable—even for enterprise teams without prior tech experience. I’ve seen firsthand how investing in Instacart clone app development can unlock new revenue streams, deepen customer loyalty, and bring real operational efficiencies.

So if you're ready to deliver convenience at scale, now’s the perfect time to build your Instacart clone app solution—and I’d love to help you take the first step.

[lunagracie01]

How to Launch a Tinder Clone App in the US in Under 30 Days

Launching a Tinder clone app in the US within 30 days may sound ambitious, but with the right approach, tools, and planning, it’s entirely achievable. Let’s get to know it shortly, 

This blog streamlines the step-by-step workflow to take you from idea to launch in under a month.

Week 1: Planning, Research & Setup

Start by conducting quick but effective market research. Identify your target demographic, analyze competitor apps, and define what makes your Tinder clone app unique. 

Are you focusing on a niche dating group?  

Ensure to select a reliable Tinder clone script that offers essential features like swiping, real-time chat, geolocation, profile verification, and admin controls. 

Check whether it allows customization, is scalable, and supports both iOS and Android platforms. By using this script, you can save weeks of development time.

Make sure you are in compliance with the law and register your company in the United States while the technical foundation is being laid. 

Establish the relevant terms and conditions, age limitations (18+), and privacy policies. Dating apps that draw users from abroad also abide by U.S. data privacy laws like the CCPA and maybe the GDPR.

Week 2: Branding, Customization & Development

Start customising the UI/UX and branding as soon as your dating script is complete. Incorporate your app's name, logo, and colour scheme, and alter the UI to reflect your business. 

The secret to drawing in and keeping users is a powerful visual aesthetic. Then, based on your findings, add or change features. 

To keep consumers interested, incorporate third-party APIs for push alerts, payment gateways (such as PayPal or Stripe), and SMS/email verification.

Behind the scenes, set up the admin panel, database, and analytics dashboard (e.g., Firebase or Mixpanel). These tools are essential for managing users, monitoring performance, and planning growth.

Week 3: Testing & Optimization

Before going live, conduct thorough quality assurance testing. Check for bugs, crashes, and performance issues across devices. 

Test all key flows like account creation, swiping, matching, chatting, blocking/reporting, and payments. 

Use both manual and automated testing tools to ensure your Tinder clone app's stability. 

After the testing process, conduct a beta launch with a small group to gather real-world feedback. This helps to identify and fix the bug easily. 

Week 4: Launch & Marketing

The time has come to launch your Tinder clone quickly.  Launch your Tinder clone app confidently in the competitive market industry. 

Launch your marketing campaign in parallel. Promote your dating app on social media platforms like Instagram, TikTok, and Facebook to meet your target audience. 

Collaborate with influencers, run paid ad campaigns, and engage on dating forums or communities to gain attraction.

Finally, set up real-time analytics to track user behavior, retention, and growth. Use this data to fine-tune your Tinder clone app post-launch and plan for future updates.

Summing Up! 

Launching a Tinder clone app in the US within 30 days is achievable with the right strategy, tools, and execution. 

By leveraging a Tinder clone script, focusing on essential features, and streamlining your development, branding, and testing phases, you can dramatically reduce time to market. 

Combine with smart marketing and legal readiness, and you're well-positioned for a successful launch. 

Whether you're targeting a niche audience or aiming for mass appeal, speed and agility are your biggest assets. 

With a clear plan and a sharp focus, your dating app goes from idea to live platform in just one month.

[clayoai]

What Is Call Screening? Everything You Need to Know in 2025

Let me take you back to a typical Monday morning.

I was gearing up for a 90-minute deep work sprint—deck open, coffee in hand, headphones on.

Then my phone buzzed.

Unknown number.

I ignored it. But in the back of my mind, a question was gnawing: “What if it’s important? A client? An investor?”

For the next 20 minutes, I wasn’t in flow—I was in limbo. And that was the moment I knew: ignoring unknown calls wasn’t enough anymore.

I needed a smarter solution. That’s when I discovered call screening—and everything changed.

📞 What Is Call Screening?

Call screening is the process of identifying, evaluating, and filtering phone calls before you decide whether to answer, reject, or forward them.

It’s like having a digital receptionist—someone who answers unknown numbers for you, checks who’s calling, and only connects the important ones to you.

Call screening used to mean listening to a voicemail or asking “Who is this?” in the early 2000s.

But in 2025?

It’s AI-powered, real-time, and essential.

🧠 How Does Call Screening Work in 2025?

Modern call screening software uses AI and databases to:

Detect and flag known spam or scam numbers.

Answer unknown calls automatically and interact with the caller.

Ask the purpose of the call and interpret the response.

Transcribe conversations in real time.

Forward or block the call based on urgency and intent.

For example, if a courier calls to confirm your delivery, your call screener can ask who they are and forward them to you with context.

If a scammer or robocall hits your number? Blocked. Logged. Forgotten.

🔍 Why Is Call Screening Important Today?

In 2025, we receive more unknown calls, spam calls, and scam attempts than ever before. These calls don’t just waste time—they create mental noise and break focus.

Whether you’re a founder, creator, or consultant, your phone is your lifeline—and your liability.

Without call screening, every unknown number becomes a distraction. And sometimes, a risk.

☠️ What Happens Without Call Screening?

Here’s what you risk:

Distraction during deep work: Even if you don’t pick up, seeing your phone ring interrupts your train of thought.

Falling for scams: AI-driven deepfake scams are common. Voice clones, urgent requests, emotional manipulation—they’re all on the rise.

Missed opportunities: Ignoring calls entirely might mean you miss a potential client or media request.

Fatigue: The mental toll of deciding whether to answer every unknown call adds up fast.

In short: no screening = no clarity.

💡 Call Screening Features That Matter in 2025

The best call screening apps go beyond blocking. They use AI and automation to protect your time without shutting the door on opportunity.

Here’s what to look for:

1. Live Screening

The software answers unknown calls for you. It can ask “Who’s calling?” or “Why are you calling?” in real time.

2. Transcription

You don’t have to listen—just read. Live text feeds show what the caller says so you can decide on the spot.

3. Caller Intent Analysis

Advanced tools (like Clayo.ai) analyze tone, keywords, and urgency to decide whether to block, forward, or summarize.

4. Spam + Scam Detection

Uses public and private databases to flag known spam, robocalls, and scam numbers.

5. Smart Summaries

If a call is legit but not urgent, you get a short summary instead of a real-time interruption.

6. CRM & Contact Integration

Links known numbers with your contact list or CRM so your team or clients never get blocked.

🏆 Best Call Screening Apps in 2025

Here are the leading tools for call screening—and what makes them different:

✅ Clayo.ai

Built for founders, creators, and consultants. Screens unknown calls, asks for intent, filters spam, detects AI-generated voices, and sends summaries. Integrates with calendars, CRMs, and even voice notes.

🟢 Best for: Professionals who want AI-powered control and peace of mind.

✅ Google Call Screen

Native on Pixel devices. Great for one-time callers. Uses voice assistant to ask “Who’s calling?” and shows responses live.

🟡 Best for: Android users who want a lightweight tool.

✅ Truecaller

Great spam ID engine. Recognizes spammy numbers based on global data. Limited intent screening.

🟡 Best for: Basic blocking and spam detection.

✅ Hiya & Nomorobo

Popular in North America. Good spam filters and number databases. Lacks advanced AI features or real-time intent handling.

🟡 Best for: U.S. users looking for robocall protection.

🧘 Why Call Screening Matters for Focus

Let’s talk brain science for a second.

The Harvard Business Review reports that even a brief notification—like a ringing phone—can reduce focus by up to 20%. And the University of California Irvine found it takes 23+ minutes to refocus after an interruption.

That’s just from seeing your phone light up.

Now imagine that happening five times a day.

Without screening, your phone becomes your biggest productivity killer.

With it? You reclaim time, clarity, and control.

👑 Why I Recommend Clayo.ai

I’ve tested Google Call Screen. I’ve used Truecaller for years. But when I needed something that worked with my business—and not just as a blocker—Clayo.ai was the answer.

It’s not just about spam detection. It’s about call intent, context, and control.

Clayo.ai:

Filters spam and robocalls

Screens unknown numbers in real-time

Uses AI to understand caller purpose

Forwards only what’s important

Summarizes the rest so I can stay in flow

It’s literally my phone assistant—and it’s smarter than most humans I’ve hired.

🔚 Final Word: You Deserve a Phone That Protects You

You protect your inbox with filters. Your calendar with scheduling links. Your time with productivity systems.

Why not your phone?

In 2025, call screening isn’t a “nice-to-have.” It’s a requirement if you want to stay focused, secure, and in control.

📱 Try Clayo.ai and stop letting unknown numbers interrupt your strategy, your momentum, and your peace.

👉 Click here to try Clayo.ai — and let your phone start working for you.

[nealkaewesi]

DATABASE ENTRY EMOTIONAL CALIBRATION CHIP (ECC-CHIP) classification class-7 neuro-programmatic construct origin iro corporate congress (defunct) application implantation in ECC (emotionally calibrated construct) infants

OVERVIEW

the ECC was a neurotechnological implant used to erase volition, enforce behavioral compliance, and synchronize emotional response across the ECC program's artificial lifeform units. installed during infancy, the chip was designed to transform engineered humanoids into obedient, networked entities capable of high-risk combat, social infiltration, or occupation support with zero independent cognition.

it was a linchpin in the iro corporate congress's forced-labor genocide campaign during the laile genocide.

STRUCTURE

programmable matter base

the ECC utilizes programmable matter fused with synthetic neural mesh to rewrite organic synaptic architecture.

enables full-body override. can inhibit or stimulate motor function at will.

adjusts genetic expression to favor rapid healing, enhanced muscular response, and endurance in M4-class (gravity differential x4) environments.

emotional calibration algorithm (ECA)

the central AI stack within the chip continuously monitors endocrine and limbic activity.

emotions are not suppressed but redirected toward productive ends (e.g., fear → loyalty, pain → mission compliance).

includes an automated information-data capture (AIDC) protocol to monitor social interaction and propagate learned responses through the network.

analysis & compliance phases

each unit undergoes daily emotion-logic recalibration, known as compliance phase cycling (CPC), ensuring no deviation from operational tolerances.

behavior is flagged, stored, and in some cases remotely corrected via fleet-ops command nodes.

PHASES OF FUNCTIONALITY

the ECC chip architecture functioned in tandem with five standardized operational states. infancy (nullphase) Full override, nonverbal, subcortical function only. no memory retention.

childhood (syncphase) language and cognitive development directed entirely by ECC-net. training protocols embedded.

adolescence (stabiphase) initiation of independent response modeling. emotional range narrowed to mission-relevant output.

combat (burnphase) full reactive sync with the ECC-net and commanders. high aggression, minimal self-preservation impulse.

dormancy (gridphase) units placed in burn grids. stasis chambers which both physically house ECCs and update collective codebases through data osmosis.

NETWORK INTERFACING

ECC chips were networked across subphase-syncpoints, forming a real-time cognitive net dubbed the ECC-net or Burn Grid. these links permitted:

instantaneous behavior cloning between nodes

remote task directives and memory override

emotional resonance syncing, often used to suppress outlier trauma

post-liberation, former ECCs report intense dissociative trauma stemming from stored echoes of others' pain and actions.

NOTABLE COMMANDS (pre-liberation)

ANALYSIS[CMD] overwrites voluntary behavior with highest priority code FREEZE[STASIS] locks unit in full-body stasis for preservation CALM[DRONE] floods pleasure centers to enforce dissociation or pacify rage KILL[VAR1-5] custom-tier threat termination protocols REPLICATE[DATA] installs recent experience into network peers SHUTDOWN[GLOBAL] emergency chip failsafe; lethal if overused

LIBERATION HISTORY

kaewesi-899 (neal kaewesi) experienced a chip grounding fault at age 20, severing him from the ECC-net and granting free will.

with assistance from starfleet and access to progenitor code on kaewesi-7, neal reprogrammed the recursive loop sustaining the ECC-net and unified all liberated units under a consensual, free-will-based network: the Kin.

CURRENT FEDERATION POSITION

all ECC technology is banned under articles 2 and 5 of the federation artificial sentience accord and the shi'kahr convention. the Kin Consensus is officially recognized as a sovereign emergent species and holds protected status.

[sethybad]

EveryAI Review 2025: Is This the Only AI Dashboard You’ll Ever Need?

In 2025, artificial intelligence tools are more powerful than ever — but managing them has become a major headache. From juggling subscriptions to learning different platforms like ChatGPT, MidJourney, Canva AI, Claude 3, and others, creators and businesses are overwhelmed. That’s where EveryAI enters the picture.

In this comprehensive review, we’ll explore what EveryAI is, how it works, its top features, pros and cons, pricing, and why it may be the ultimate solution for marketers, freelancers, and even beginners looking to dive into the AI space.

🔍 What is EveryAI?

EveryAI is an all-in-one AI dashboard that provides access to over 350 top-tier AI tools under a single interface. Imagine using ChatGPT, Claude AI, Google Gemini, MidJourney, Canva AI, Runway ML, ElevenLabs, and more — without needing separate accounts or integrations. EveryAI simplifies your digital workflow by eliminating the need to hop from one app to another.

Whether you’re a content creator, business owner, developer, or someone starting their online journey, EveryAI helps automate tasks and enhance productivity — without requiring any technical experience.

GET ACCESS FREE

🌟 Key Features of EveryAI

Here’s what makes EveryAI truly stand out in the crowded AI market:

✅ Access to 350+ Premium AI Tools

EveryAI connects you to a massive library of powerful models for generating text, designing graphics, coding software, editing videos, creating music, and more.

✅ No Monthly Fees

Unlike other AI platforms, EveryAI operates on a one-time payment model. You get lifetime access — no recurring charges.

✅ Commercial Rights Included

You can use EveryAI to create and sell AI-generated content or services and keep 100% of your earnings.

✅ Voice & Text Search

Whether you type or speak your request, EveryAI understands and fetches the best AI model to perform the job.

✅ One-Click Execution

Create logos, ads, videos, websites, avatars, ebooks, and more — without leaving the dashboard.

✅ Built-In Chatbot Builder

Create your own branded AI assistant tailored to your niche or business.

✅ Content Repurposing Engine

Turn videos into articles, blog posts into reels, or images into slideshows — all with just a few clicks.

✅ Works for All Niches

Freelancers, affiliate marketers, ecommerce owners, YouTubers, agencies, and beginners will find value in EveryAI’s flexibility.

⚙️ How Does EveryAI Work?

Using EveryAI is surprisingly easy. Here’s a step-by-step breakdown:

Login  Access the dashboard from your laptop, tablet, or mobile device.

Search  Enter or speak your task, such as “generate blog post,” “create YouTube thumbnail,” or “build sales funnel.” EveryAI then scans its model database and suggests the ideal tool.

Execute  Click to launch the selected tool and let it complete the task. You can design, code, write, animate, and build — all without switching tabs.

The entire process is seamless and beginner-friendly. No coding, no complicated setup, no need to pay for APIs.

🧪 My Experience with EveryAI

As someone who reviews digital products regularly, I had the opportunity to test EveryAI extensively. I approached it with skepticism — could a single dashboard truly replace multiple AI subscriptions?

Here’s what I discovered:

First Impressions: The interface was clean and well-organized by categories such as writing, design, video, and coding.

Functionality: When I typed “Create a product mockup with logo,” EveryAI automatically launched Canva AI and Leonardo AI. Within seconds, I had a professional-looking image.

Content Creation: Writing a landing page using DeepSeek and ChatGPT was a breeze. It cut my usual writing time by 70%.

Video Production: I tested the video creation by prompting “Create 8K promo video for a fitness app.” Runway ML and Pika Labs produced a stunning video in under 2 minutes.

Voice Cloning: Using ElevenLabs, I replicated my voice and turned an article into a narrated avatar video.

Website Building: In one session, I created an ecommerce store layout, sales funnel, and promotional materials without touching code.

Everything worked together flawlessly. It was like having a virtual AI assistant team on call 24/7.

💰 EveryAI Pricing & OTO Breakdown

Here’s the complete pricing structure for EveryAI:

ProductPriceFront-End (FE)$16 (one-time)OTO 1: Unlimited$67OTO 2: Done-For-You$297OTO 3: Automation$47OTO 4: Swift Profits$47OTO 5: Limitless Traffic$97OTO 6: Agency License$167OTO 7: Franchise Edition$97OTO 8: Multiple Income Streams$47

🟢 Discount Coupons Available:

EVERYAIADMIN — 30% off full funnel

EVERYAI5OFF — $5 off

🎁 Bonuses are also offered for those who purchase the front-end and upsells.

👥 Who Should Use EveryAI?

EveryAI is ideal for:

Freelancers — Create and sell content, graphics, and websites with ease.

Digital Marketers — Generate ads, landing pages, and video promos effortlessly.

Ecommerce Store Owners — Build product pages, images, mockups, and funnels.

Affiliate Marketers — Create promotional content fast.

Agencies — Fulfill client orders faster with automation and scalability.

Beginners — Launch digital services or content businesses with no experience.

Content Creators — Produce blogs, videos, and social posts on autopilot.

📋 Pros and Cons

Pros:

✅ Access to 350+ top AI tools

✅ No need for coding or API connections

✅ One-time payment, lifetime access

✅ Commercial rights to resell AI services

✅ Super fast execution and easy interface

✅ Great for beginners and experts

Cons:

❌ May feel overwhelming at first due to feature variety

❌ Requires constant internet access

❌ Some advanced users might prefer individual tool control

❓ Frequently Asked Questions

Q. Do I need any experience to start using EveryAI?  No experience needed — if you can type or speak, you can use EveryAI.

Q. Do I need to buy anything else?  No. EveryAI includes everything within the platform.

Q. Are there monthly fees?  Only if you miss the limited-time deal. Act early to secure the lifetime access.

Q. How fast can I start making money with EveryAI?  Some users report results within the first day by selling AI-generated content.

Q. What if I don’t like it?  There’s a 30-day money-back guarantee, so your purchase is risk-free.

🧠 Final Verdict: Is EveryAI Worth It?

Absolutely. EveryAI isn’t just a collection of tools — it’s a complete AI operating system designed for the modern digital entrepreneur. It simplifies complex tasks, eliminates tool fatigue, and empowers you to create and grow fast.

For less than $20, you get access to hundreds of AI technologies that would otherwise cost thousands per year. Whether you’re building a brand, managing clients, or starting from scratch, EveryAI provides a scalable, cost-effective solution.

If you want to save time, cut costs, and stay ahead in the AI revolution — EveryAI is the smartest investment you can make in 2025.

GET ACCESS FREE

[clonetab]

Automate your DBA Operation with clonetab software.

Are high storage costs and lengthy refresh times slowing down your database management? It's time to make a change.

Join with clonetab software and ✅ Save up to 80% on storage ✅ Achieve up to 95% savings in refresh costs & time ✅ Effortlessly clone multi-TB databases – including 10TB ERP systems in under 1 hour!

Reduce your annual cost and streamline your DBA processes. Ready to optimize your operations and drive efficiency?

Let’s make it happen with clonetab software. comment below for demo

[aishuglb12]

Databricks Revolutionizes Data and AI Landscape with New Operational Database, Free Education, and No-Code Pipelines

San Francisco, CA – June 12, 2025 – Databricks, the pioneering Data and AI company, today unveiled a suite of transformative innovations at its Data + AI Summit, setting a new benchmark for how enterprises and individuals interact with data and artificial intelligence. The announcements include the launch of Lakebase, a groundbreaking operational database built for AI; a significant $100 million investment in global data and AI education coupled with the Databricks Free Edition; and the introduction of Lakeflow Designer, empowering data analysts to build production-grade pipelines without coding. These advancements underscore Databricks’ commitment to democratizing data and AI, accelerating innovation, and closing the critical talent gap in the industry.

Databricks Unveils Lakebase: A New Class of Operational Database for AI Apps and Agents

What is it?

Databricks announced the launch of Lakebase, a first-of-its-kind fully-managed Postgres database built for AI. This new operational database layer seamlessly integrates into the company’s Data Intelligence Platform, allowing developers and enterprises to build data applications and AI agents faster and more easily on a single multi-cloud platform. Lakebase is powered by Neon technology and is designed to unify analytics and operations by bringing operational data to the lakehouse, continuously autoscaling compute to support demanding agent workloads.

When is the Launch Planned?

Lakebase is now available in Public Preview, marking a significant step towards its full availability.

Who Introduced?

Ali Ghodsi, Co-founder and CEO of Databricks, introduced Lakebase, stating, “We’ve spent the past few years helping enterprises build AI apps and agents that can reason on their proprietary data with the Databricks Data Intelligence Platform. Now, with Lakebase, we’re creating a new category in the database market: a modern Postgres database, deeply integrated with the lakehouse and today’s development stacks.”

Why Does This Matter? Motivation: The Driving Forces Behind

Operational databases (OLTP) represent a $100-billion-plus market, yet their decades-old architecture struggles with the demands of modern, rapidly changing applications. They are often difficult to manage, expensive, and prone to vendor lock-in. AI introduces a new set of requirements: every data application, agent, recommendation, and automated workflow needs fast, reliable data at the speed and scale of AI agents. This necessitates the convergence of operational and analytical systems to reduce latency and provide real-time information for decision-making. Fortune 500 companies are ready to replace outdated systems, and Lakebase offers a solution built for the demands of the AI era.

Business Strategies

The launch of Lakebase is a strategic move to create a new category in the database market, emphasizing a modern Postgres database deeply integrated with the lakehouse and today’s development stacks. This strategy aims to empower developers to build faster, scale effortlessly, and deliver the next generation of intelligent applications, directly addressing the evolving needs of the AI era.

Key benefits of Lakebase include:

Separated compute and storage: Built on Neon technology, it offers independent scaling, low latency (<10 ms), high concurrency (>10K QPS), and high availability transactional needs.

Built on open source: Leveraging widely adopted Postgres with its rich ecosystem, ideal for workflows built on agents as all frontier LLMs have been trained on vast database system information.

Built for AI: Enables launch in under a second and pay-for-what-you-use pricing. Its unique branching capability allows low-risk development by creating copy-on-write database clones for developer testing and agent-based development.

Integrated with the lakehouse: Provides automatic data sync to and from lakehouse tables, an online feature store for model serving, and integration with Databricks Apps and Unity Catalog.

Enterprise ready: Fully managed by Databricks, based on hardened compute infrastructure, encrypted data at rest, and supports high availability, point-in-time recovery, and integration with Databricks enterprise features.

Lakebase Momentum

Digital leaders are already experiencing the value, with hundreds of enterprises having participated in the Private Preview. “At Heineken, our goal is to become the best-connected brewer. To do that, we needed a way to unify all of our datasets to accelerate the path from data to value,” stated Jelle Van Etten, Head of Global Data Platform at Heineken. Anjan Kundavaram, Chief Product Officer at Fivetran, added, “Lakebase removes the operational burden of managing transactional databases. Our customers can focus on building applications instead of worrying about provisioning, tuning and scaling.” David Menninger, Executive Director, ISG Software Research, highlighted that “By offering a Postgres-compatible, lakehouse-integrated system designed specifically for AI-native and analytical workloads, Databricks is giving customers a unified, developer-friendly stack that reduces complexity and accelerates innovation.”

Partner Ecosystem

A robust partner network, including Accenture, Airbyte, Alation, Fivetran, and many others, supports Lakebase customers in data integration, business intelligence, and governance.

Read More : Databricks Revolutionizes Data and AI Landscape with New Operational Database, Free Education, and No-Code Pipelines

[wafi-news2024]

AI-Powered Cyber Attacks: How Hackers Are Using Generative AI 

Introduction 

Artificial Intelligence (AI) has revolutionized industries, from healthcare to finance, but it has also opened new doors for cybercriminals. With the rise of generative AI tools like ChatGPT, Deepfake generators, and AI-driven malware, hackers are finding sophisticated ways to automate and enhance cyber attacks. This article explores how cybercriminals are leveraging AI to conduct more effective and evasive attacks—and what organizations can do to defend against them. 

How Hackers Are Using Generative AI

1. AI-Generated Phishing & Social Engineering Attacks

Phishing attacks have become far more convincing with generative AI. Attackers can now: 

Craft highly personalized phishing emails using AI to mimic writing styles of colleagues or executives (CEO fraud). 

Automate large-scale spear-phishing campaigns by scraping social media profiles to generate believable messages. 

Bypass traditional spam filters by using AI to refine language and avoid detection. 

Example: An AI-powered phishing email might impersonate a company’s IT department, using natural language generation (NLG) to sound authentic and urgent.

2. Deepfake Audio & Video for Fraud

Generative AI can create deepfake voice clones and videos to deceive victims. Cybercriminals use this for: 

CEO fraud: Fake audio calls instructing employees to transfer funds. 

Disinformation campaigns: Fabricated videos of public figures spreading false information. 

Identity theft: Mimicking voices to bypass voice authentication systems. 

Example: In 2023, a Hong Kong finance worker was tricked into transferring $25 million after a deepfake video call with a "colleague." 

3. AI-Powered Malware & Evasion Techniques

Hackers are using AI to develop polymorphic malware that constantly changes its code to evade detection. AI helps: 

Automate vulnerability scanning to find weaknesses in networks faster. 

Adapt malware behavior based on the target’s defenses. 

Generate zero-day exploits by analyzing code for undiscovered flaws. 

Example: AI-driven ransomware can now decide which files to encrypt based on perceived value, maximizing extortion payouts. 

4. Automated Password Cracking & Credential Stuffing 

AI accelerates brute-force attacks by: 

Predicting password patterns based on leaked databases. 

Generating likely password combinations using machine learning. 

Bypassing CAPTCHAs with AI-powered solving tools. 

Example: Tools like PassGAN use generative adversarial networks (GANs) to guess passwords more efficiently than traditional methods. 

5. AI-Assisted Social Media Manipulation 

Cybercriminals use AI bots to: 

Spread disinformation at scale by generating fake posts and comments. 

Impersonate real users to conduct scams or influence public opinion. 

Automate fake customer support accounts to steal credentials. 

Example:AI-generated Twitter (X) bots have been used to spread cryptocurrency scams, impersonating Elon Musk and other influencers. 

How to Defend Against AI-Powered Cyber Attacks 

As AI threats evolve, organizations must adopt AI-driven cybersecurity to fight back. Key strategies include: 

AI-Powered Threat Detection – Use machine learning to detect anomalies in network behavior. 

Multi-Factor Authentication (MFA) – Prevent AI-assisted credential stuffing with biometrics or hardware keys. 

Employee Training – Teach staff to recognize AI-generated phishing and deepfakes. 

Zero Trust Security Model – Verify every access request, even from "trusted" sources. 

Deepfake Detection Tools – Deploy AI-based solutions to spot manipulated media. 

Conclusion  Generative AI is a double-edged sword—while it brings innovation, it also empowers cybercriminals with unprecedented attack capabilities. Organizations must stay ahead by integrating AI-driven defenses, improving employee awareness, and adopting advanced authentication methods. The future of cybersecurity will be a constant AI vs. AI battle, where only the most adaptive defenses will prevail.

Source Link:https://medium.com/@wafinews/title-ai-powered-cyber-attacks-how-hackers-are-using-generative-ai-516d97d4455e