The incident raises a much bigger question:

As companies give AI more power to solve problems automatically, are we also giving hackers a new way to manipulate those systems?

A Real 2026 Incident Involving an AI Support System

In June 2026, security researchers reported that attackers had abused Meta’s AI-powered support chatbot to help take over Instagram accounts.

According to TechCrunch, attackers reportedly manipulated the support chatbot into accepting claims of account ownership. In some cases, the system helped change the email address associated with targeted accounts. Once attackers controlled the recovery email, they could potentially take further steps to take over the account. Meta later said it had fixed the issue.

The incident became particularly interesting because some of the targeted accounts were notable or high-profile profiles.

Ars Technica also reported on the incident and the targeting of valuable Instagram usernames.

The important point is not simply that an Instagram account was compromised.

The bigger lesson is that an attacker may sometimes exploit the logic of an automated system instead of directly breaking through its security.

The New Meaning of “Hacking”

When most people hear the word hacking, they imagine someone stealing a password or installing malware.

Modern cybercrime can be much more complicated.

An attacker may exploit an API, manipulate an automated process, abuse an account-recovery mechanism, steal a session token or convince a system to perform an action that should have required stronger verification.

In other words, the attacker does not always need to break the door if they can convince the security system to open it.

That becomes especially important when AI is placed between the user and sensitive backend systems.

Why AI Changes the Security Equation

Traditional software normally follows rules created by developers.

AI systems can interpret language, evaluate context and generate responses dynamically.

That flexibility makes AI extremely useful. At the same time, it creates a new security challenge.

Suppose an AI support agent is allowed to help users recover accounts.

It may have access to identity information, account records and recovery functions.

Now imagine an attacker successfully convinces the AI that they are the legitimate account owner.

The AI makes a wrong decision.

The backend follows the AI’s instruction.

A conversation has suddenly become a security incident.

A Small Development Mistake Can Become a Big Attack

This is where software development becomes extremely important.

A developer may create a feature that looks completely normal during testing.

For example, the requirement might be:

“Allow genuine users to recover their accounts quickly.”

The developer builds the feature, tests several normal scenarios and confirms that everything works.

However, one question may have been missed:

“What happens if someone deliberately tries to fool the system?”

That missing test can become the attacker’s opportunity.

When a Bug Becomes a Human Problem

Developers often describe problems using technical terms such as bug, vulnerability or configuration error.

Users experience the consequences differently.

A small access-control problem could expose private messages, photographs, business information or financial details.

Consequently, the chain can become:

Small bug → Security weakness → Account takeover → Data loss → Real-world damage

For an ordinary person, losing a social-media account may mean losing years of memories.

For a creator or business owner, the same incident could affect customers, income and reputation.

Why AI-Generated Code Needs Human Review

AI can write code much faster than a developer working manually.

Nevertheless, generated code is not automatically secure simply because it compiles or passes a basic test.

A function may work correctly with normal input but behave dangerously when an attacker provides unexpected input.

Similarly, AI may generate authentication logic that appears reasonable but fails to properly verify permissions.

For this reason, developers should review AI-generated code before using it in production.

They should understand what the code does rather than simply copying the answer from an AI assistant.

The Danger of Sharing Production Data With AI

There is another risk that developers can easily overlook.

Imagine a developer receives a production error and wants AI to explain it.

They copy the entire log into an AI tool.

Unfortunately, that log contains a customer email address, internal API information, a session identifier or another confidential value.

The developer was trying to solve a bug.

Instead, sensitive information may have been unnecessarily exposed.

Therefore, developers should remove or mask confidential information before using real-world logs or code in AI prompts.

Never Paste These Secrets Into an AI Prompt

Developers should be particularly careful with:

• Passwords
• API keys
• Private keys
• Database credentials
• JWT secrets
• Production tokens
• Customer personal information
• Private source code
• Internal documents
• Authentication codes
• Confidential business information

Instead, replace real values with safe dummy data whenever possible.

For example, a real production password should never be included simply to help an AI explain a connection error.

AI Agents Need the Right Permissions

The risk becomes even greater when AI agents can perform actions instead of merely providing answers.

An AI coding agent might have access to a repository, terminal, browser, cloud environment or deployment system.

That can be extremely powerful.

However, unnecessary permissions increase the possible damage from a mistake, compromised environment or malicious instruction.

Therefore, organisations should follow the principle of least privilege.

If an AI only needs to read a file, it should not automatically receive permission to delete files.

Likewise, an AI working in a development environment should not automatically receive unrestricted production access.

Why “Fix It Later” Can Become Expensive

Security problems are often cheaper to fix during development than after release.

A vulnerability found before deployment may require a code change and another round of testing.

Once the same vulnerability reaches production, the situation becomes much more complicated.

The company may need to investigate the incident, identify affected users, analyse logs, deploy an emergency patch and monitor the system.

Moreover, the technical fix may not undo the damage that already occurred.

A database can be secured again.

A leaked password can be changed.

However, lost trust is much harder to recover.

Third-Party Packages Can Create Another Risk

AI may recommend a library because it appears to solve a programming problem quickly.

That does not mean the package should automatically be installed.

Before adding a dependency, developers should check whether it is trustworthy, maintained and necessary.

They should also look for known vulnerabilities and understand what permissions the package requires.

After all, an application can be secure at the source-code level and still become vulnerable through a compromised dependency.

What Developers Should Do Before Releasing AI-Assisted Code

A safer workflow can include:

Requirement → Security review → AI-assisted coding → Human code review → Unit testing → Integration testing → Security testing → Dependency scanning → Secret scanning → Staging → Final review → Production

This process may take more time than simply generating code and deploying it.

However, a few additional hours of security testing can prevent much larger problems later.

What Normal Users Can Do to Stay Safe

You do not need to become a cybersecurity expert to protect your online accounts.

Start with the basics.

Use a different strong password for important services.

Enable multi-factor authentication whenever it is available.

Keep your email account especially secure because it is often used to recover other accounts.

Also, review login notifications and connected applications regularly.

Never Trust an Unexpected Support Message

Attackers frequently pretend to be customer-support representatives.

They may claim that your account has a security problem and ask you to verify information.

Some may send a link that looks legitimate but leads to a fake website.

Therefore, never share passwords, OTPs or recovery codes simply because someone claims to be support.

When in doubt, open the official application or website yourself instead of using a link supplied by a stranger.

What to Do If Your Account Is Compromised

Act quickly if you notice suspicious activity.

First, change the password from a trusted device.

Next, enable or reset multi-factor authentication.

Then review recent login activity and remove unknown sessions or connected applications.

If the attacker changed recovery information, use the platform’s official account-recovery process.

The FTC also recommends changing compromised passwords, signing out of other sessions and enabling two-factor authentication when recovering hacked accounts.

The Future of Cybercrime May Look Different

The next generation of cyberattacks may not always look like traditional hacking.

Some attacks may involve AI manipulation, automated social engineering, malicious prompts, compromised AI agents or abuse of automated customer-support systems.

As AI becomes connected to more real-world services, the potential attack surface also grows.

That means security teams must start asking not only whether an AI system can answer correctly, but whether it can be manipulated into taking the wrong action.

The Most Important Lesson for Developers

AI is not automatically the enemy.

In fact, AI can help developers identify bugs, write tests, analyse logs and improve software.

The danger begins when speed replaces verification.

A developer should never assume that AI-generated code is secure simply because it works.

Likewise, an organisation should never give an AI system unlimited access simply because automation is convenient.

Use AI for productivity, but keep humans responsible for security decisions.

Final Thoughts

The 2026 Instagram account-takeover incident offers a powerful warning about the changing nature of cybercrime.

Attackers do not always need to steal a password directly.

Sometimes, the weakness can be hidden inside an automated process.

Sometimes, the problem can be a small development mistake.

Sometimes, the biggest risk is not the AI itself but the permissions surrounding it.

For developers, the message is clear:

Review the code. Protect the data. Limit permissions. Test unexpected behaviour.

For ordinary users, the rules are equally simple:

Use strong passwords. Enable MFA. Protect your email. Never share OTPs or recovery codes. Be suspicious of unexpected support requests.

Technology will continue to become smarter.

Cybersecurity must become smarter with it.

Because the next major cyberattack may not begin by breaking into the system. It may begin by convincing the system to open the door itself.

The post AI Cybercrime and Account Takeover: How Hackers Exploit AI Security appeared first on Pijus.

When you open Google, YouTube, Facebook, or another website on your phone, the data does not travel directly from your phone to the company’s server. It moves through several interconnected networks.

Understanding this journey makes it much easier to understand Wi-Fi, routers, ISPs, IP addresses, data centers, BGP, and Internet routing.

Step 1: Your Phone Connects to the Wi-Fi Router

Your phone first communicates wirelessly with your home Wi-Fi router.

For example:

Phone → Wi-Fi → Home Router

The Wi-Fi connection uses radio signals. Your phone and router exchange small units of data called packets.

Your router acts as the first gateway between your local network and the wider Internet.

Step 2: Your Router Connects to Your ISP

Your home router normally connects to your Internet Service Provider (ISP), such as Airtel, Jio, or another broadband provider.

The connection may use:

• Fiber optic cable
• Ethernet
• AirFiber or fixed wireless technology
• Other access technologies

So the basic path becomes:

Phone → Home Router → ISP Network

Your home router is only the first part of the journey. Large ISP networks contain many routers and other networking equipment.

Step 3: The ISP’s Network Routes Your Data

Once your request enters the ISP’s network, ISP routers determine where the packets should go next.

For example, if you request a YouTube video:

Phone → Home Router → ISP → Google/YouTube Network

The ISP does not necessarily send every request through one particular router. Modern networks have multiple routes and interconnected locations.

Step 4: How Does Google Connect to an ISP?

Google and an ISP such as Jio or Airtel can connect their networks through network interconnection.

This can involve:

• Direct peering
• Private network interconnections
• Internet Exchange Points (IXPs)
• Transit providers
• High-speed fiber infrastructure

This means Google’s network and the ISP’s network can exchange Internet traffic.

It is not necessarily:

Google Server → One Main Center → Jio

Instead, modern Internet infrastructure is distributed across many locations.

Step 5: Google’s Data Centers Are Connected

Google operates a large global infrastructure consisting of data centers, network locations, edge infrastructure, servers, and its own backbone network.

Different Google services and systems can communicate across this infrastructure.

A simplified model is:

Google Data Center → Google Network/Backbone → Interconnection → ISP Network

There is not one single “Google main server” through which every request must pass.

Step 6: Routers Don’t Store the Internet

A common misunderstanding is that routers contain Google’s, YouTube’s, or Facebook’s data.

They normally don’t.

A router’s primary job is to forward packets toward their destination.

Think of a router like a traffic junction:

It does not contain every destination; it helps decide which direction traffic should take.

Servers and storage systems are responsible for storing and processing application data.

Step 7: What Happens When You Watch YouTube?

Suppose you tap a YouTube video.

A simplified request path could look like:

Phone
↓
Home Wi-Fi Router
↓
ISP Network
↓
Internet Interconnection
↓
Google/YouTube Network
↓
Server or nearby cache/CDN
↓
Response travels back toward your phone

The exact route can vary.

In many cases, content may be delivered from a nearby CDN or edge location, rather than from a distant central server.

Step 8: Why Does the Response Come Back?

Your phone sends a request containing network information needed to deliver the traffic to the correct destination.

The destination system processes the request and sends data back.

The response can travel through:

Google/YouTube → Interconnected Networks → ISP → Home Router → Wi-Fi → Phone

Importantly, the return path does not have to be exactly identical to the path used by the outgoing packets.

Internet routing is dynamic.

Step 9: What Is BGP?

One of the most important technologies behind large-scale Internet routing is BGP (Border Gateway Protocol).

Different organizations operate their own networks, called autonomous systems.

BGP helps these networks exchange information about which IP address ranges are reachable through them.

In simplified form:

Network A:
“I can reach these IP networks.”

Network B:
“I can reach those IP networks.”

Routers use this routing information to determine suitable paths for Internet traffic.

This is one of the reasons the Internet can function as a huge collection of interconnected networks rather than one centrally controlled network.

Wi-Fi, SSID and BSSID: Where Do They Fit?

These terms belong mainly to the local wireless connection between your device and an access point.

SSID

SSID = Wi-Fi network name

Example:

MyHomeWiFi

BSSID

BSSID = identifier of a specific Wi-Fi access point, commonly represented by its MAC address.

Example:

AA:BB:CC:11:22:33

MAC Address

A MAC address identifies a network interface at the link layer.

Your phone’s Wi-Fi interface can have a MAC address, and a router’s Wi-Fi interface can have its own MAC address.

Therefore:

SSID ≠ BSSID ≠ your phone’s MAC address

They have different purposes.

Can Wi-Fi Help Estimate Location?

Yes, but this is different from Internet routing.

A phone can sometimes scan nearby Wi-Fi access points without actually connecting to them.

It may observe information such as:

SSID + BSSID + signal characteristics

Location systems can use Wi-Fi information together with other signals and databases to estimate an approximate location.

However, simply scanning a Wi-Fi network does not mean the router automatically receives the phone’s GPS coordinates.

Similarly, a router’s connection log and a Wi-Fi location database are two different things.

What Happens When You Disconnect From Wi-Fi?

When your phone disconnects from a Wi-Fi network, the router may retain connection logs depending on its configuration.

Such logs can potentially contain information such as:

• Device identifier or MAC address
• Connection time
• Disconnection time
• Network activity information

But a router cannot automatically follow your phone after it leaves its Wi-Fi coverage.

If your phone later connects to another Wi-Fi network, that other network may have its own connection records.

The Internet Is Not One Giant Computer

This is perhaps the most important idea to remember.

The Internet is a network of networks.

It includes:

• Home networks
• Mobile networks
• ISPs
• Enterprise networks
• Cloud networks
• Content providers
• Data centers
• Internet Exchange Points
• Backbone networks
• Transit networks

These networks cooperate through standardized networking technologies.

That is what allows your small home router to communicate with enormous services such as Google, YouTube, Facebook, and thousands of other online platforms.

The Complete Journey in One Diagram

📱 Phone
   ↓ Wi-Fi
📡 Home Router
   ↓
🌐 ISP Access Network
   ↓
🌐 ISP Core Routers
   ↓
🔗 Peering / Transit / Interconnection
   ↓
☁ Google / Meta / Other Network
   ↓
🖥 Server / Data Center / CDN
   ↓
🔁 Response
   ↓
🌐 ISP
   ↓
📡 Home Router
   ↓ Wi-Fi
📱 Phone

The Big Picture

Your phone does not directly “connect to Google” through one single cable.

Instead, your request travels through multiple interconnected networks, with routers forwarding packets toward their destinations.

That is the hidden infrastructure behind the simple action of opening a webpage or watching a video.

Your Wi-Fi router connects you to your ISP. Your ISP connects to other networks. Those networks connect to services such as Google through peering, private interconnection, Internet exchanges, or transit. Google’s distributed infrastructure then processes and delivers the requested data.

Understanding this journey gives students a practical foundation for learning Computer Networks, Internet Architecture, Cybersecurity, Cloud Computing, Networking, and Web Technologies.

The post How the Internet Works, Wi-Fi Router to Google Server appeared first on Pijus.

This simple feature is actually an important part of modern Wi-Fi scanning and location technology.

How Does Wi-Fi Scanning Work?

Your smartphone contains a Wi-Fi radio that continuously searches for available wireless networks when Wi-Fi scanning is enabled.

Nearby Wi-Fi routers and access points broadcast information that can be detected by your phone. The phone can identify details such as the network name (SSID) and the access point’s identifier, commonly called a BSSID/MAC address.

The password is only required when your phone tries to establish a protected connection.

In simple words:

Detecting Wi-Fi ≠ Connecting to Wi-Fi

Your phone can see a Wi-Fi network without having permission to join it.

Can Wi-Fi Help Your Phone Know Your Location?

Yes. Wi-Fi information can sometimes help smartphones estimate their location, particularly when GPS signals are weak.

For example, inside a building, GPS may become less accurate because satellite signals have difficulty reaching the device. Nearby Wi-Fi networks can provide additional clues about where the phone is.

Location systems can compare information about nearby Wi-Fi access points with location databases and use that information as one part of a location estimate.

This is why your phone can sometimes determine your approximate location even when you are indoors.

Why Is Wi-Fi Scanning Useful?

Wi-Fi scanning is not only about finding free internet. It can support several everyday smartphone functions:

• Faster location estimation
• Indoor positioning
• Finding nearby Wi-Fi networks
• Improving location accuracy when GPS is weak
• Helping apps and services understand the device’s approximate environment

Modern phones may combine Wi-Fi information with GPS, Bluetooth, mobile networks, sensors and other signals to improve location accuracy.

Does Your Phone Know the Wi-Fi Password?

No.

Simply detecting a Wi-Fi network does not reveal its password.

A router can broadcast information that identifies its wireless network, but a protected Wi-Fi connection still requires authentication.

So, if your phone displays:

“Home_WiFi – Secured”

it has detected the network, but it does not automatically know the password.

What About Privacy?

This technology also raises an important privacy question.

Wi-Fi-related information can contribute to location estimation, and location data can reveal where a device may be. That’s why smartphone operating systems provide location and Wi-Fi scanning controls.

You should regularly review:

• Which apps have location permission
• Whether an app really needs location access
• Wi-Fi and Bluetooth scanning settings
• Your phone’s overall privacy permissions

You don’t have to understand every technical detail to protect your privacy. Checking app permissions regularly is one of the simplest privacy habits you can develop.

The Interesting Part

Your phone doesn’t necessarily need a satellite signal to get useful information about where you are.

It can combine clues from the world around it:

Wi-Fi + GPS + Mobile Network + Bluetooth + Sensors → Location Estimate

That means the small Wi-Fi icon on your phone represents much more than an internet connection. It is also part of a larger system that helps modern smartphones understand their surroundings.

Final Thought

The next time your phone finds a Wi-Fi network that you have never connected to, remember: it hasn’t necessarily accessed the network—it has simply detected its wireless signal.

The password protects the connection; Wi-Fi scanning helps the phone discover what is around it.

And that small difference is one of the hidden technologies behind today’s smart location systems.

The post How Your Phone Detects Wi-Fi Without Knowing the Password appeared first on Pijus.

What if a machine could sense that you are nearby without touching you? That is where interaction sensors come in.

An interaction sensor detects changes around it—such as movement, touch, distance, heat, or the presence of an object—and sends a signal to an electronic system.

A common example is the PIR motion sensor. It detects changes in infrared radiation caused by moving people or animals. This is why it is widely used in automatic lights, security systems, smart homes, and IoT projects.

Other sensors work differently. Ultrasonic sensors measure distance using sound waves, while capacitive sensors can detect touch or proximity by sensing changes in electrical capacitance.

The interesting part is that these tiny components allow ordinary devices to react to the world around them automatically.

From turning on a light when someone enters a room to helping robots detect obstacles, interaction sensors are a small but essential part of today’s connected technology.

The post Interaction Sensors – The Tiny Technology Behind Smart Devices appeared first on Pijus.

The growth of AI has been remarkably fast. Stanford’s 2026 AI Index reports that generative AI reached 53% population adoption within three years—faster than the personal computer or the internet reached comparable adoption milestones.

What Is Artificial Intelligence?

Artificial Intelligence is a technology that enables computers and software systems to perform tasks that normally require human intelligence.

These tasks include:

• Understanding language
• Recognizing images and speech
• Writing and analyzing information
• Generating images and videos
• Writing computer code
• Finding patterns in large amounts of data
• Making predictions and recommendations
• Automating complex workflows

Modern AI is moving beyond simply answering questions. AI agents are increasingly being designed to use tools, interact with software, and complete multi-step tasks with less human intervention. IBM describes this shift as a move toward AI systems and agents rather than simply focusing on individual AI models.

Why Is AI Growing So Fast?

Several factors are responsible for the rapid growth of AI.

1. Powerful Computing

Modern GPUs, cloud computing, and specialized AI chips allow companies to train and run increasingly capable AI systems.

2. Huge Amounts of Data

AI systems can learn patterns from enormous collections of text, images, audio, video, and other information.

3. Better AI Models

AI models have become much better at understanding language, reasoning, generating content, and working with multiple types of information.

4. AI Is Becoming Easier to Use

People no longer need to be AI researchers to use AI. A normal user can simply type a question or instruction and receive an answer, create an image, analyze a document, or generate computer code.

AI Is Changing the Workplace

One of the biggest effects of AI is happening in the workplace.

Companies are using AI to automate repetitive tasks, analyze information, support customers, generate content, write code, and improve productivity.

In India, AI is already becoming an important part of the IT industry. The Indian government has highlighted AI’s role in productivity, innovation, jobs, and the country’s digital economy.

However, AI does not simply mean that every human job will disappear.

Instead, many jobs are likely to change.

For example, a software tester may use AI to generate test cases, analyze failures, create automation scripts, and summarize test results. A developer can use AI coding assistants to generate initial code and then spend more time reviewing, testing, and improving it.

The important skill of the future may therefore not be AI versus humans, but humans working effectively with AI.

AI Agents: The Next Big Step

Traditional chatbots mainly respond to questions.

The next generation of AI is moving toward AI agents.

An AI agent can potentially:

1. Understand a goal.
2. Break the goal into smaller tasks.
3. Select appropriate tools.
4. Perform actions.
5. Check the results.
6. Continue until the task is completed.

This could transform areas such as software development, customer service, research, finance, healthcare administration, and business operations.

Gartner identifies agentic AI, domain-specific models, smaller reasoning models, and multimodal AI as important trends in the next phase of generative AI adoption.

AI and Software Development

Software development is one of the industries experiencing significant AI-driven change.

Developers can now use AI to:

• Generate code
• Explain existing code
• Find bugs
• Create unit tests
• Write documentation
• Convert code between programming languages
• Generate SQL queries
• Analyze logs
• Create prototypes

But generated code still needs human review.

AI can produce code that looks correct while containing logical errors, security problems, incorrect assumptions, or unnecessary complexity. Research on AI-assisted repositories also suggests that while generative AI can reduce some code-generation effort, it can shift work toward validation, debugging, documentation, and maintenance.

Therefore, programming fundamentals remain extremely important.

AI in Education

AI is also changing education.

Students can use AI to:

• Understand difficult concepts
• Practice programming
• Summarize lessons
• Generate questions
• Learn languages
• Receive explanations at different difficulty levels

However, students should use AI as a learning assistant rather than simply copying its answers.

The real value of education is still understanding why something works.

AI in Healthcare

AI has the potential to help healthcare professionals analyze medical information, support diagnosis, discover patterns, and accelerate research.

But healthcare is a sensitive field. AI systems must be carefully tested, validated, and monitored because incorrect information can have serious consequences.

AI should therefore support qualified professionals rather than blindly replace human judgment.

AI and Cybersecurity

AI is becoming increasingly important in cybersecurity.

Security teams can use AI to:

• Detect suspicious activity
• Analyze large volumes of logs
• Identify unusual behavior
• Prioritize security alerts
• Assist with threat intelligence
• Automate parts of incident response

At the same time, attackers can also use AI to create more sophisticated attacks.

This creates an ongoing race between attackers and defenders.

The Risks of AI

AI brings enormous opportunities, but it also creates risks.

Some important concerns include:

• Job displacement
• Fake images and videos
• Deepfakes
• Privacy problems
• Cybersecurity threats
• Misinformation
• Biased AI systems
• Overdependence on AI
• Incorrect AI-generated information

The rapid adoption of AI makes responsible development particularly important. Recent discussions around enterprise AI have also emphasized security, privacy, governance, and trustworthy deployment.

Will AI Replace Humans?

This is one of the biggest questions surrounding AI.

The answer is more complicated than simply saying “yes” or “no.”

AI is very good at certain tasks, particularly repetitive information-processing tasks. But humans still provide creativity, emotional understanding, responsibility, leadership, judgment, communication, and real-world experience.

Some jobs may disappear or shrink, while completely new roles may emerge.

The more realistic future is likely to involve significant changes in how people perform their jobs.

The Future Belongs to AI + Humans

The biggest lesson from the current AI revolution is that learning how to work with AI is becoming increasingly valuable.

Instead of asking:

“Will AI take my job?”

a better question may be:

“How can I use AI to become better at my job?”

A software engineer who understands AI tools can potentially work faster. A designer can use AI for rapid prototypes. A business owner can automate repetitive operations. A student can use AI as a personalized learning assistant.

AI is becoming another powerful tool in the technology toolbox.

Conclusion

Artificial Intelligence is growing at an extraordinary speed and is already changing technology, business, education, software development, cybersecurity, and everyday life.

The future of AI will not be determined only by how powerful the technology becomes. It will also depend on how responsibly people use it.

AI can automate tasks, increase productivity, and create new opportunities—but human judgment will remain essential.

The people who learn how to understand, use, evaluate, and work alongside AI may be among the best prepared for the next era of technology.

AI is not just changing the future. It is changing the present—and the transformation has already begun.

The post The Rapid Growth of Artificial Intelligence and How AI Is Changing Our Future appeared first on Pijus.