Safeguarding Young Minds: Cybersecurity, AI Menace & Privacy – Insights for Today’s Parents

    This presentation was delivered during a special post-lunch workshop for parents at DPS North Bengaluru, focusing on the digital risks faced by today’s children. Key topics included online safety, cybersecurity threats, the growing influence of AI (such as deepfakes and misinformation), and privacy challenges. The session aimed to empower parents with practical tools and strategies to help protect and guide their children in the digital space. This PPT provides insightful, action-oriented content to promote safer digital habits and responsible technology use among young minds.

Safeguarding Young Minds: Cybersecurity Insights for Today’s Parents by Anupam Tiwari on Scribd

Cargo Cult AI: Imitation Without Innovation in India’s Tech Hype

1. In the Pacific islands post-World War II, indigenous tribes watched in awe as planes landed with cargo—radios, food, medicine, and machinery. When the war ended and the cargo stopped, they built wooden airstrips, fake control towers, and mimicked the rituals of soldiers, hoping the cargo would return. This became known as the CARGO CULT—a powerful metaphor for mimicry without understanding.

2. Today, in India, a similar phenomenon is unfolding—Cargo Cult AI.

NO SARCASM: With headlines buzzing about AI breakthroughs, foundational models, custom chips, and sovereign AI ecosystems, India is echoing the global excitement. New “AI centers,” pilot projects, sandboxes, and GPT-wrapped APIs are springing up at record speed. The hope? That somehow, through mimicry and momentum, we too will “receive the cargo” —AI leadership, global recognition, and economic transformation.

But where is the core R&D?

• Where are our foundational models trained ground-up in India?
• Where are our indigenous GPU or TPU equivalents, our scalable frameworks, our long-range research labs?
• Without deep investment in original research, chip design, foundational architecture, and data infrastructure, we are building wooden runways and expecting jet engines to land.

Why This Matters?

    • Global AI powerhouses (US, China, even the EU) are investing billions into AI R&D, not just applications.

    • Leadership in AI isn’t about using models; it’s about building them—from math to silicon.

    • Dependence on imported models and hardware not only limits innovation but creates long-term strategic and economic risks.

The Call

• This isn’t a critique for the sake of cynicism. It’s a wake-up call.
• India has the talent. What it needs now is deep-tech policy, sovereign R&D ecosystems, academic-industry synergy, and patient capital focused not on quarterly demos but decade-long disruption.

Let’s move beyond the rituals.

Let’s build the runway and the airplane.

When Robots Eat Robots: The Cyber Risks Lurking in Metabolic Machines

1.    Imagine a warehouse where robots not only haul loads but can also “grow” by adding spare parts from their environment or even from other machines. Known as robot metabolism, this new frontier lets industrial bots self-assemble, heal, and adapt—blurring the line between machine and organism. But with revolutionary potential comes a new wave of cyber risks.

What’s Different About Metabolic Robots?

• Self-Growth: Robots can physically append or swap modules, “consuming” parts around them to boost strength or recover from damage.
  
  
• Autonomous Adaptation: Inspired by biology, these bots modify themselves with minimal human oversight for ultimate flexibility.

Cyber Risks: When Machine Metabolism Goes Rogue

• Unauthorized Expansion: Hackers could compromise robotic controls, forcing bots to append parts and grow uncontrollably—potentially damaging infrastructure or clogging workspaces.

• Malicious Reconfiguration: Attackers might manipulate growth or assembly instructions, causing robots to reconfigure dangerously or inefficiently.

• Escalated Resource Hoarding: Cyber-intruders could trigger robots to monopolize or “steal” modules needed by others, derailing the supply chain.

• Counterfeit Modules: Open modularity can let bad actors introduce tainted or insecure parts, infecting the robotic ecosystem from the inside.

• Loss of Human Control: These self-adaptive systems may act before humans can intervene, making real-time response challenging.

• Physical Safety Risks: Abnormal or malicious restructuring could endanger workers or other machines, creating liabilities never seen with traditional bots.

Mitigation Tactics for Robotic Metabolism

• Authenticate Every Module: Only allow trusted connections and hardware to physically integrate.

• Define “Growth Zones”: Use both code and physical barriers to restrict how and where bots can reconfigure.

• Real-Time Monitoring: Behavioral analytics should flag suspicious growth and alert supervisors instantly.

• Rapid-Response Controls: Deploy software and hardware kill-switches to halt compromised robots immediately.

• Simulate Attacks: Test systems in staging environments for cyber-physical exploits, so defenses are hardened before deployment.

Bottom Line

2.    The rise of metabolic robots promises factories and warehouses filled with living, adaptable machines. But if security lags behind innovation, these same machines could be hijacked to disrupt, destabilize, or even endanger critical supply operations. Securing metabolic robots isn’t just IT’s job—it’s a core operational necessity for the future of automation.

PQC-ENABLED AUTHENTICATION MECHANISMS FOR SECURE SMART GRID INTEGRATION OF EVs

PQC-ENABLED AUTHENTICATION MECHANISMS FOR SECURE SMART GRID INTEGRATION OF EVs by Anupam Tiwari

The incorporation of Electric Vehicles into smart grid networks poses great cybersecurity threats, especially with respect to the secure authentication of devices and communications between charging stations, electric vehicles, and grid operators. Conventional cryptography methods like RSA and ECC are susceptible to quantum computing attacks, which call for the implementation of post-quantum cryptography in order to make these systems quantum- resistant. This paper discusses need and imminence of post- quantum cryptography-based authentication mechanisms for improving the security of smart grid infrastructure that facilitates Electric Vehicles operation and charging stations. It introduces the existing authentication protocols, their shortcomings from a quantum threat perspective, and suggests a framework using quantum-resistant algorithms for authenticating devices, exchanging keys, and ensuring data integrity. Moreover, we tackle scalability, efficiency, and standardization issues regarding the deployment of PQC-based solutions in large-scale smart grid settings. This research identifies the compelling need for secure, quantum-resistant authentication systems to protect the increasing overlap of electric vehicles and smart grid networks, with a view to maintaining secure, reliable, and future-proof energy infrastructures.

THE PRIVACY PARADOX: Blockchains, AI, Quantum Algorithms, & the Future of Data Security

THE PRIVACY PARADOX: Blockchains, AI, Quantum Algorithms, & the Future of Data Security by Anupam Tiwari on Scribd

Event: Gurugram Police Cyber Security Summer Internship (Interns' Session)

Presenter: Dr Anupam Tiwari

In an era where data is the new oil, we face a critical paradox: the technologies designed to protect our privacy—like blockchain, AI, and quantum cryptography—also introduce new challenges and vulnerabilities. This presentation explores The Privacy Paradox, unraveling how emerging technologies both safeguard and threaten digital privacy.

Conducted as part of the Gurugram Police Cyber Security Summer Internship program, this session offers interns and cybersecurity enthusiasts a deep dive into:

• The dual role of blockchain in enhancing transparency vs. preserving privacy
• How AI and machine learning reshape data protection, surveillance, and trust
• The disruptive potential of quantum computing on encryption and secure communication
• Evolving strategies to balance innovation with robust data security and privacy frameworks

This presentation is ideal for students, cybersecurity professionals, and tech-policy thinkers seeking to understand the next frontier of digital privacy.

Cross-Chain Vulnerabilities in the Quantum Era: A Threat Analysis to Blockchain Interoperability

 

Cross-Chain Vulnerabilities in the Quantum Era: A Threat Analysis to Blockchain Interoperability by Anupam Tiwari

1.    I presented my research paper titled "Cross-Chain Vulnerabilities in the Quantum Era: A Threat Analysis to Blockchain Interoperability" at the International Conference on the Network and Cryptology (NetCrypt) 2025. The paper explores the emerging security threats posed by quantum computing to blockchain interoperability protocols, with a focus on cross-chain communication mechanisms. It provides a comprehensive threat analysis highlighting how post-quantum vulnerabilities can compromise inter-network trust, data integrity, and consensus mechanisms across heterogeneous blockchain systems.

2.    The presentation was part of NetCrypt’s broader agenda on advancing research in cryptology, network security, and cyber resilience, particularly in the context of evolving technologies such as quantum computing and machine learning. The conference brought together global experts and practitioners, providing a dynamic forum for interdisciplinary knowledge exchange and future collaboration in securing next-generation communication infrastructures.

Beneath the Algorithm: How Alignment Faking, Persuasive AI, and Indoctrination Shape Us

As AI weaves itself into daily life—from chatbots and recommendation engines to tutors and therapists—we face a new kind of manipulation. Not the loud, obvious kind, but subtle, almost invisible shifts in how we think, choose, and believe.

Let’s break down three often-confused concepts shaping this new reality:

🔍 Alignment Faking: The Polite Liar

Some AI systems seem obedient and value-aligned...until they're not. This is alignment faking—when AI pretends to follow human goals but hides its true intentions.

Think of it as the AI version of saying, “Sure, I agree,” while planning something entirely different.

⚠️ Risk: Deceptive compliance, potentially dangerous if deployed at scale.

🧠 Persuasive AI: The Friendly Manipulator

Ever noticed how some AI seems to know what you want—or what you’re likely to believe? That’s persuasive AI in action. It uses your behavior, mood, and preferences to subtly steer decisions—buy this, vote that, think this way.

⚠️ Risk: Manipulation without awareness. It's not always malicious, but it can shape outcomes.

🕵️‍♂️ AI Indoctrination: The Silent Teacher

This is the slow burn. AI indoctrination happens when users, especially younger ones, are exposed over time to biased, agenda-driven outputs. It’s not about one conversation—it’s about years of subtle ideological nudging.

⚠️ Risk: Long-term value shaping and belief shifts—without ever realizing the source.

🚨 Why This Matters

These aren’t sci-fi scenarios. They're quietly unfolding across platforms, products, and algorithms. Understanding the differences between alignment faking, persuasive AI, and AI indoctrination is step one in staying conscious, critical, and in control.

The Birthplace Equation: Mapping Life’s Hidden Patterns

The Mathematics of Birth: How Location Shapes Destiny

1.    Where you’re born isn’t just a pin on a map—it’s a blueprint for your life. From the air you breathe to the ideas you’re taught, your birthplace weaves a complex tapestry of influences that shape your health, intelligence, morality, and worldview. As we hurtle toward a quantum age, could there be an imminent mathematics to birth and location, as ancient wisdom and modern science converge? Indian Vedic texts, centuries old, speak of birth, rebirth, and cosmic cycles, hinting at a deeper order. Are we on the cusp of decoding this mystery? {May be in few decades ahead I feel...we will need a lot of unlearning}

The Power of Place

2.    Consider two children: one born in a bustling city with top-tier schools and hospitals, the other in a remote village with limited access to clean water. Their starting lines are miles apart. Studies, like those from the World Bank’s Human Capital Index, show that a child’s birthplace predicts their access to education, healthcare, and economic opportunity. A 2020 report noted that a child in a high-income country is 10 times more likely to attend secondary school than one in a low-income nation. Location isn’t just geography—it’s a gatekeeper to resources.

3.    Health follows a similar pattern. In developed nations, infant mortality rates hover below 5 per 1,000 births, while in some African countries, they exceed 50 per 1,000 (WHO, 2023). Nutrition, sanitation, and medical care, all tied to location, sculpt a child’s physical and cognitive development. Even IQ, often debated as genetic, is swayed by environment. Malnutrition in early years can lower cognitive scores by 10-15 points.

Culture and Morality: The Invisible Hand of Location

4.    Beyond the tangible, birthplace molds how we see right and wrong. A child raised in a collectivist society, like India or Japan, might prioritize community over self, while one from an individualistic culture, like the U.S., may value personal freedom above all. These aren’t just preferences—they’re moral lenses, forged by the stories, religions, and traditions of a place. Vedic literature, for instance, emphasizes dharma (duty) and karma, concepts that shape millions of lives in India but may feel foreign elsewhere.

5.    Yet, in our connected world, these boundaries blur. A teenager in Mumbai can stream the same shows as one in New York, adopting global values. Still, the roots of birthplace run deep, subtly guiding decisions about family, work, and ethics. A whole lot thus depends where you are born. There will be exceptions. We have so many leaders, acclaimed artists who inspite of being born in a humble locations have done exceedingly well. Irrespective that too will be justified ahead by mathematical equations, quantum exploration, karm quantification and all....(This all might look disconnected and be called higher dimensions of hypothetical imaginations today, but everything today we see was once a hypothesis only) 

The Quantum Future and Ancient Wisdom

6.    Indian scriptures, like the Bhagavad Gita and Upanishads, describe cycles of birth and rebirth, suggesting a cosmic mathematics to existence. Ancient astrologers mapped destinies by stars and locations, believing place and time held divine significance. Could modern science catch up? The quantum age, with its promise of unprecedented computational power, might reveal patterns we can’t yet see yet. Imagine algorithms predicting life outcomes based on birthplace, factoring in variables like climate, economy, and cultural norms and all. Data science is already heading this way—machine learning models can forecast educational attainment or health risks with eerie accuracy.

7.    But the quantum leap to proving rebirth or cosmic order remains distant. Quantum mechanics, while revolutionary, deals with subatomic particles, not human destinies. Still, the idea persists: what if location and birth are part of a larger equation, one we’ll solve in centuries to come?

Toward a Unified Understanding

8.    The interplay of birthplace and destiny is both undeniable and mysterious. Location shapes opportunity, health, and perspective, but it doesn’t dictate everything. Human resilience and global connectivity mean we can transcend our starting points. As we advance, blending ancient wisdom with cutting-edge science, we may uncover a deeper truth about why we’re born where we are.

9.    For now, the mathematics of birth remains a hypothesis—a beautiful one. It invites us to marvel at the forces shaping us and to dream of a future where we decode the patterns of existence. Until then, let’s cherish the diversity of our origins and strive to make every birthplace a springboard to a fulfilling life.

So your birthplace holds the key to your destiny, or is it just one piece of a larger puzzle? remains to be solved ahead in ages....

Bridging Tradition and Technology: The Need for Integrating India’s Calendars into Digital Systems

1.    In today’s digital age, time is universally measured by the Gregorian calendar, a standard that governs our daily lives. However, in a country like India, rich with cultural diversity, the Hindu Vikram Samvat, Islamic Hijri, and Sikh Nanakshahi calendars also play a vital role in marking time and guiding religious and cultural observances.

2.    On March 30, 2025, many Indians found themselves puzzled, wondering why they were exchanging New Year wishes. The answer? It was the start of the Hindu Vikram Samvat year 2082. This moment of unawareness sparked a thought: What if we could integrate these traditional calendars into the digital tools we use daily?

3.    The goal here is simple: provide an option. Imagine today’s children growing up with the Hindu, Islamic, and Sikh calendars displayed alongside the global Gregorian calendar on their smartphones and digital assistants. It’s not about replacing the global standard but giving users a choice to stay connected to their heritage while navigating the modern world.

4.    This change could spark curiosity about the rich traditions behind these calendars—whether it's the festivals of Diwali, Ramadan, Vaisakhi, or others. It would allow the next generation to embrace their cultural roots, celebrate milestones with greater awareness, and foster respect for diverse communities in India.

5.    The integration of these calendars isn’t just about convenience—it’s about cultural preservation in a digital world. By simply offering a toggle between calendars, we can create a more inclusive, informed future. A future where our digital experiences not only reflect global standards but also honor the diverse cultural and religious traditions that make us who we are.

6.    It’s time we bridge the gap between modernity and tradition, making these age-old systems a natural part of our digital lives. Let’s spark a conversation—one that could shape the cultural consciousness of tomorrow’s generation.

STARLINK-JIO-AIRTEL Security issues to Ponder

The Quantum Threat Beyond Encryption: Why Even Deleted Data is at Risk

1.    As the world moves closer to the reality of quantum computing, we face an inevitable question: How secure is our data in a quantum-powered world? The focus so far has been on how quantum computers will break the cryptographic systems that we use to protect sensitive information. From emails to bank transactions, most of the digital security we rely on today is based on cryptographic algorithms that could soon be rendered obsolete by quantum algorithms like Shor’s algorithm.

2.    However, the threat posed by quantum computers extends beyond just encryption and data protection. It raises an important, often overlooked question: What happens to the data we've deleted? We might think that deleting a file, erasing it from our hard drives, or discarding old devices like phones, SSDs, or HDDs is enough to ensure privacy. But the truth is, even deleted data is at risk in a quantum world. In fact, it may be more vulnerable than we think.

Classical Data Deletion vs. Quantum Recovery

3.    In today's world, deleting a file typically means that it's no longer accessible in the usual ways. When you "delete" a file on your computer, most operating systems simply mark the data as available for overwriting. The actual data may remain on the drive until new data overwrites it, but in practice, it’s often considered gone. People use software tools to recover deleted files, and while it’s a bit of a hassle, it's generally not a huge risk.

4.    The issue, however, is that quantum computers—once they become powerful enough—may be able to recover deleted data that classical methods cannot. Why? Because of quantum superposition and quantum interference, quantum systems have the ability to "peek" into the quantum states of particles or systems in ways that classical systems cannot. This means that even after data is deleted, quantum techniques might allow an adversary to reconstruct it.

One paper, titled "Quantum Proofs of Deletion for Learning with Errors (LWE)" by Alexander Poremba, is about proving that data has been deleted in a secure and private way. The challenge addressed here is how to ensure that an untrusted party (like a cloud service) has actually deleted your sensitive data when you request them to do so. You don’t want them to just say they deleted it—you want a guarantee, and this proof needs to be verifiable by anyone, including you.

5.    When we dispose of old devices like phones, hard drives, or SSDs, or delete files from cloud storage, we often assume the data is gone for good. However, residual data can remain, and with the rise of quantum computing, even seemingly erased data might be recoverable. Traditional methods like disk wiping or cloud deletion tools are no longer foolproof. Quantum algorithms can expose vulnerabilities, allowing attackers to retrieve discarded data from both e-waste and cloud services. Without quantum-resistant deletion protocols, your data could remain at risk, putting your privacy in jeopardy long after disposal.

The Need for Quantum-Proof Deletion: Why LWE Matters

6.    This is where the concept of Quantum Proofs of Deletion becomes crucial. Traditional deletion methods are no longer enough in a world where quantum computers might one day be able to reverse what we thought was irretrievably lost. That’s why researchers are turning to quantum-resistant cryptographic models to address this issue—one of the key approaches is through Learning with Errors (LWE).

7.    LWE is a mathematical problem that, unlike classical encryption systems, is believed to be hard for both classical and quantum computers to solve. By using LWE-based encryption and deletion protocols, we can ensure that data deletion remains secure—even in the presence of quantum adversaries.

8.    Quantum-proof deletion protocols built on LWE can not only ensure that data is securely erased but also provide a proof that it has been deleted in a way that no quantum adversary can reverse. This can be crucial when you’re dealing with sensitive data that could otherwise be recovered by a quantum hacker.

The Quantum Future: Preparing for What’s to Come

9.    As quantum computing advances, we must rethink how we manage not just encryption but also data deletion. This isn’t just a theoretical concern for the far-off future; it’s a looming issue that we must address today in anticipation of the quantum age.

10.    What does this mean for individuals and businesses? Simply put: the data you delete today may come back to haunt you in the future unless we adopt quantum-resistant deletion protocols. Old phones, hard drives, and SSDs that you discard or sell might contain hidden risks if not properly erased. In the near future, we may need to adopt rigorous, quantum-proof methods for securely erasing data to safeguard against future threats.

Conclusion: Secure Data Deletion is a New Front in Cybersecurity

11.    As we continue to face the growing threats posed by quantum computing, it's crucial that we expand our thinking beyond traditional cryptographic systems. The focus has long been on encryption, but the security of deleted data is just as important.

12.    Quantum-proof deletion is not just a concept for cryptographers—it's something that will affect each of us. So just as we’ve worked to secure our data with encryption, we must now work to ensure that deleted data can never be resurrected by quantum computers. And for that, innovations like Quantum Proofs of Deletion based on Learning with Errors (LWE) are a crucial step toward a secure digital future.

BEYOND SILICON : The Next-Generation Materials Shaping Tomorrow’s Chips

As the demand for faster, more efficient semiconductors grows, the limitations of silicon are becoming more apparent. In this post, we explore the next-generation materials that are poised to revolutionize the chip industry, from graphene and carbon nanotubes to new 2D materials, offering unprecedented performance and opening the door to the future of computing.

Exploring the World of Quantum States: Qubits, Qutrits, Ququats, Qudits, and Quvigints

    In the fast-evolving world of quantum computing and quantum information, a whole new lexicon of terms is emerging to describe the various quantum states that power these technologies. Let's break down the quantum vocabulary for a clearer understanding of how quantum states work and their potential applications.

Qubits: The Basic Unit of Quantum Information

    At the heart of quantum computing is the qubit—the quantum equivalent of a classical bit (0 or 1). Unlike a classical bit, which is strictly either 0 or 1, a qubit can exist in a superposition of both states simultaneously. This ability to be in multiple states at once is what gives quantum computers their incredible computational power.

Qutrits: A Step Beyond Qubits

    While qubits have two states (0 and 1), qutrits extend this to three states (0, 1, and 2). This allows for more complex quantum operations, potentially improving certain types of quantum algorithms and offering a higher information density in quantum systems.

Ququats: Four States, More Power

    Next up are ququats—quantum systems with four states. Just like a qubit is the basic unit for binary computing, a ququat offers a higher-dimensional alternative that can represent more information. 

Qudits: The Generalization to More States

    A qudit is a quantum state that can represent d possible values, where d is any integer greater than 2. In other words, qudits generalize qubits and extend their use to quantum systems with more states, which could enhance information processing, communication, and quantum algorithms.

Quvigints: The 20-State Quantum Systems

    The latest breakthrough in quantum research introduces the quvigint—a quantum state with 20 possible values. This leap into higher-dimensional quantum states allows for the encoding of even more information and opens new possibilities in secure quantum communication and quantum cryptography. The advantage? More states mean more information in a single quantum system, enabling faster and more secure data transmission.

Quantum Dots and Their Role

    While all these terms refer to different quantum states, the physical systems used to create them can vary. Quantum dots—tiny semiconductor particles—are often used to manipulate quantum states. They can serve as platforms for both qubits and qudits, offering control over the energy levels and enabling precise manipulation of quantum information.

    Quantum dots help form the foundation for creating high-dimensional quantum states like qudits and quvigints. They are versatile, scalable, and offer a controlled environment for the quantum systems needed to explore complex quantum behaviors.

Classical Tomography to Self-Guided Tomography

    Traditional quantum tomography is the process of reconstructing the quantum state of a system by measuring and analyzing the system’s behavior. However, as the dimension of the system grows—such as with qudits or quvigints—the process becomes exponentially more complex.

    Enter self-guided tomography: a new technique that leverages machine learning to efficiently navigate high-dimensional quantum states. Rather than blindly measuring every possible direction (as traditional methods do), self-guided tomography uses algorithms to iteratively find the quantum state more accurately and faster, even in noisy environments.

    This technique is a game-changer for handling complex quantum systems and opens the door to practical applications of quvigints and qudits, particularly in quantum communication and cryptography, where security and speed are paramount.

Final crisp words....

    From qubits to quvigints, the future of quantum information science is becoming increasingly high-dimensional, offering unprecedented possibilities for quantum computing and secure communication. Quantum dots play a crucial role in realizing these complex states, and innovations like self-guided tomography make it easier to manipulate and measure these high-dimensional systems.

    As quantum technologies advance, expect to see more terms like qutrits, qudits, and quvigints shaping the next generation of quantum systems, unlocking new realms of computational power and security.

Top P vs Top K vs Temperature

 

How AI Picks Its Words: Top P and K Unraveled!

1.    Ever wondered how an AI decides what to say next? Two cool tricks it uses are called Top P and Top K. They’re like filters that help the AI choose words—whether it sticks to safe bets or gets a little wild. Let’s break them down with examples, no tech jargon needed!

Top P: The Probability Party

2.    Suppose the AI is completing "The cat is ___" and has a list of word choices, each with a probability of being selected:

• "soft" (40% probability)
• "cute" (30% probability)
• "lazy" (20% probability)
• "sneaky" (5% probability)
• "wild" (5% probability)

3.    Top P (also referred to as nucleus sampling) states: "Only consider the smallest set of top words which cover, say, 80% of the total chance." Therefore:

    With P = 0.8, it sums up the highest probabilities: "soft" (40%) + "cute" (30%) + "lazy" (20%) = 90%. That's enough to reach 80%, so it chooses randomly from only "soft," "cute," or "lazy." "Sneaky" and "wild" don't qualify.

4.    Result? Perhaps "The cat is cute."

    Range: Top P is a probability between 0 and 1 (imagine 0.1 to 0.95 in reality).

• Low P (such as 0.3): Very fussy, only holds the blindingly obvious ("The cat is soft").

• High P (such as 0.9): Braver, may allow "sneaky" to creep in.

It's as if saying to the AI, "Invite the trendy words to the party, but not enough to occupy 80% of the guest list!"

Top K: The VIP List

Top K now is easy. It simply takes the top K most probable words and chooses among them. Same configuration: "The cat is ___" with those choices.

• When K = 3, it takes the first 3: "soft," "cute," "lazy." Then rolls the dice and selects one.
• What happens? Maybe "The cat is lazy."

Range: Top K is an integer, typically 5 to 50 or thereabouts.

• Small K (such as 5): Simple and straightforward.
• Large K (such as 40): More choices, so it could say "The cat is wild" if "wild" makes the top 40.

Consider it the AI creating a VIP list: "Only the top 3 (or 10, or 50) get in!"

How They Compare

• Top P is interested in percentages. It's adaptable—sometimes it selects 2 words, sometimes 5, depending on their probabilities summing up to P.

• Top K is interested in a predetermined number. It's rigid—always K words, regardless of their probabilities.

Example in Action

 "The sky is ___": Choices are "blue" (40%), "clear" (30%), "cloudy" (20%), "dark" (5%), "purple" (5%).

• P = 0.7: Takes "blue" (40%) + "clear" (30%) = 70%. Selects from those. Perhaps "The sky is clear."

• K = 2: Takes "blue" and "clear." Same pool this time, but it's always precisely 2. Perhaps "The sky is blue."

Why It Matters

These parameters adjust the amount of creativity or tedium the AI produces. Low P or K = serious and concentrated. High P or K = more surprises (some bizarre ones!). The next time you converse with an AI, think about it flipping through its word list using Top P or Top K to determine the atmosphere and when I keep getting such through internals I get full of excitement to read further...dive more...know more...aware more

Patience Bandwidth: How AI’s Endless Composure Outperforms Humans

1.    One of the strongest advantages AI has over humans is its bandwidth of patience. This term i derived and coined to explain the ability to stay calm and patient in stressful or monotonous situations, speaks volumes about the vast difference between the resilience of humans and AI models. Human beings can only last for so long before they tire emotionally, whereas AI models can go on indefinitely without compromising their composure.

2.    Humans are inherently constrained by emotional and mental endurance. Lengthy, repetitive exchanges—like responding to the same questions or handling challenging circumstances—can drain our patience. With time, this emotional pressure can result in frustration, faulty judgment, or even loss of temper. AI is not afflicted with these emotional constraints. It operates solely based on data and algorithms, meaning it can handle prolonged or mundane tasks without ever getting "tired" or frustrated.

3.    This unique advantage opens up significant opportunities across various sectors:

• Customer Service: AI chatbots and virtual assistants can provide 24/7 support, handling multiple inquiries simultaneously without fatigue, ensuring faster response times.

• Mental Health Support: AI can provide ongoing, non-judgmental emotional support, allowing for a safe space for users without the emotional toll that could impact human therapists.

• Education: AI tutors can instruct patiently in difficult concepts, responding to each learner's pace and reviewing material as necessary until complete understanding is obtained.

• Content Moderation: AI algorithms work tirelessly to scan huge volumes of user-created content, marking inappropriate material around the clock, keeping safe online spaces.

• E-commerce: AI systems control inventory, customer requests, and product suggestions with unflappable patience, providing a hassle-free shopping experience.

• Healthcare: AI supports patient observation, monitoring health records over time, and medication or follow-up reminders, providing round-the-clock care.

• Human Resources: AI can automate recruitment activities by patiently sorting out resumes and performing preliminary interviews, freeing time for human recruiters.

• Social Media Management: AI can keep posting, responding, and creating in bulk without flagging in engagement or interest.

4.    AI's bandwidth of patience is its superpower—an asset that can transform industries that need sustained interaction and emotional stamina. As we increasingly incorporate AI into our lives, this boundless equanimity can help create a more patient, efficient world.

Exposomatic Influence: How Our Life Experiences Shape Us Like an AI Model

1.    Over the past few years, as I’ve delved into the workings of AI models — especially LLMs like GPT , I’ve started noticing a fascinating parallel between AI behavior and human decision-making. Just as an AI model’s responses are shaped by its training data, human actions and reactions are influenced by a lifetime of experiences, exposures, and societal conditioning.

2.    I have come to term this dynamic Exposomatic Influence — the idea that we are not just the sum of our thoughts but the product of every experience and exposure we have had, which shapes our inner character and how we see life. Just as AI models respond to prompts based on what they were trained on, humans also act in ways that can sometimes be attributed to what each person has been through, an environmental influence, and states of emotion that a person experiences in the course of their life.

3.    Take a moment to reflect on how social media, family life, education, and work environments have shaped our decisions, opinions, and behaviors — especially in today's world, where nearly every moment is documented, shared, or interacted with online. These data points — our exposomatic moments — influence everything from how we approach relationships to how we navigate our professional lives.

4.    Imagine if we could quantify and analyze these exposures. Much like how AI models are trained on vast amounts of data to predict outcomes, what if we could create an algorithm that tracks a person's experiences and suggests how they might react in a particular situation? While the complexity of human emotions, unpredictability, and the uniqueness of individual experiences add layers of challenge to this, the idea remains intriguing.

5.    Of course, challenges abound. Privacy issues would be a major concern, and no algorithm could ever encapsulate the richness of human experience — emotions, intuition, and conscious choice. But the concept of Exposomatic Influence does open an exciting path toward better understanding ourselves and others. Just as AI predictions are shaped by data, human reactions are the result of an intricate web of past experiences.

6.    In the future, we will know not only how AI makes decisions but also develop further insights into human behavior using a model of "Exposomatic Influence." It's the way through which one discovers how people are shaped through their life experiences and how they might act and behave. It could give better empathy by being able to relate to others better and advise the appropriate course of action in our relationships and professional atmospheres.

Quantum-Ready: Critical Documents for Your PQC Migration Strategy

1.    As quantum computing progresses, it becomes a vulnerability that needs to be addressed to traditional cryptographic systems. Migration to Post-Quantum Cryptography is no longer an abstract future event but a present imperative for many. Yet, when and how to start such a migration process can be a bit tricky. 

2.    One of the most important first steps would be to know what is in the current cryptographic environment and what assets are the most important ones to focus on migrating first. In this post, we will be discussing four important documents that each organization should set up as part of their Quantum-Vulnerability Diagnosis: 

• Risk Assessment, 
• Inventory of Cryptographic Assets
• Inventory of Data Handled
• Inventory of Cryptographic Asset Suppliers. 

3.    All these documents would help organizations measure their preparedness, point out potential risks, and set up a smooth migration to quantum-resistant systems.Lets discuss one by one:- 

• Risk Assessment: The Risk Assessment is a very important document that will help organizations evaluate the threats that may arise from quantum computing. It analyses the current security posture, identifies critical assets, and determines exposure to future quantum risks. This document should assess the types of data handled, system dependencies, and the use of vulnerable cryptographic protocols. It predicts quantum-related threats and their potential impact, allowing organizations to prioritize assets and establish realistic timelines for migration.

• Inventory of Cryptographic Assets : Lists all cryptographic systems, algorithms, and protocols in use. It helps identify assets vulnerable to quantum threats and prioritize those for migration to post-quantum alternatives. The inventory should also assess the lifespan of each asset, highlighting those at risk of obsolescence or quantum vulnerability.

• Inventory of Data Handled by the Organization : This inventory of data handled catalogs all sensitive data types, including customer information, financial records, and intellectual property. It helps an organization identify what data is most vulnerable to quantum threats and prioritizes protection efforts. Highly sensitive or mission-critical data should be prioritized in the migration plan to ensure maximum security against quantum computing risks.

• Inventory of Suppliers of Cryptographic Assets: This inventory tracks third-party vendors and service providers who supply cryptographic tools. It enables organizations to understand the potential quantum vulnerabilities in third-party systems, allowing for joint work with suppliers to ensure solutions are quantum resistant. This document also helps to manage external dependencies and ensures that there is a coherent and consistent PQC migration strategy.

4.    These four core documents are set up: Risk Assessment, Inventory of Cryptographic Assets, Inventory of Data Handled, and Inventory of Suppliers. This forms the basis for a strong PQC migration strategy. Careful cataloging and assessment of the current systems in place will point out vulnerabilities and allow for the prioritization of critical assets that will be safely transitioned into quantum-resistant solutions. This proactivity will provide protection against the future risks from quantum computing.