augustablog

[augustablog]

Personal Reflection

When I first started learning about emerging technology, I thought improvements in technology were expected and progressed in a straight line. I believed professionals could accurately predict future trends. I also saw my interaction with technology as mostly passive, using it without considering its broader implications on society, ethnics or personal growth. My perspective has since changed. I now recognize that technology evolves unpredictably due to breakthroughs, regulations and adoption trends. I have become more critical of technological developments, questioning their impact and ethical considerations rather than just accepting them.

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Neuromorphic chips

This is really interesting; they are actually computer processors designed to work like human brain not in software but in hardware. They mimic how neurons and synapses actually fire, process and store information. (AI with a brain and not just code)

The emerging real-world use cases are for brain-computer interfaces, autonomous vehicles and drones, robotics and edge AI.

The challenges of this are that it is still in research or early production stage, it need new programming models and scaling them to brain-level complexity is tough but not impossible.

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Digital Twin

I was made to understand that digital twin is a virtual replica of a physical system that constantly update with real-time data from sensors or other systems to reflect what's going on in the real world.

It is like a smart simulation that's always in sync with the real things, if something changes in the physical world, its reflected instantly in the digital world.

it is mostly used in smart cities for monitoring traffic, in manufacturing for predicting when machines need maintenance before they breakdown, and in so many other sectors.

One of it challenges is that it is closely tied to real-world systems which poses a security concern.

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PROJECT PRESENTATION

This week in class we presented our group project on evaluation tool. we assessed a small business to identify the business gap within that organization. We also suggested three emerging technologies that when adopted can help to overcome that gap. we made this based on 18 criteria which comprises of both qualitative and quantitative criteria. We evaluated the three and AI powered solution was the best to solve the gap present in that organization.

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Edge Computing

This week in class we learnt about Edge Computing. Edge computing processes data near its source instead of relying on centralized cloud servers. This minimizes latency and reduces bandwidth use. Key applications include:

IoT devices – Smart homes, industrial automation, healthcare.

Autonomous Vehicles – Real-time decision-making for navigation.

Smart Cities – Optimized traffic control, surveillance, and energy grids.

By keeping data processing local, edge computing enhances security, speeds up operations, and reduces cloud dependency. Always looking forward to the next topic.

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Computer Security

This week in class, we learned about computer security, which is accomplished using the CIA triad. Threat assessment is the process of evaluating and verifying the likelihood of threats. The first step in threat assessment is identifying the vulnerabilities of the target. To do this, the type of threat must be known. Vulnerabilities include unprotected systems, end-of-life software, and bring-your-own-device (BYOD) policies. Types of threats can be classified as malicious vs. accidental and internal vs. external attackers. Additionally, threats can involve different types of attacks, such as physical attacks, social engineering attacks, and logical attacks. Threat mitigation refers to the tools, processes, and strategies that organizations use to manage and reduce security risks. Looking forward to next week for more topic.

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Internet of Things

This week in class, we explored the fascinating world of the Internet of Things (IoT) and its impact on modern technology. IoT refers to the interconnected network of physical devices that communicate and exchange data over the internet. These devices include smart home gadgets, industrial sensors, wearable technology, and even smart cities. My key take home from the module were:

How IoT Works – IoT devices use sensors, connectivity, and cloud computing to collect and analyze data, enabling automation and real-time decision-making.

Applications of IoT – We discussed various industries leveraging IoT, including healthcare (smart monitors), agriculture (precision farming), and transportation (smart traffic systems).

Security Challenges – As IoT expands, so do security risks. We learned about vulnerabilities such as weak authentication, data privacy concerns, and the need for strong encryption.

Future of IoT – The growth of 5G, AI, and edge computing will continue to shape IoT, making it faster, smarter, and more efficient.

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Quantum Computing

This week, the instructor discussed about the above topic. I was made to understand that a quantum computer is that which exploits quantum phenomena. Unlike classical computers, which use binary bits, quantum computers utilize qubits that can exist in multiple states simultaneously (superposition) and influence each other instantly (entanglement).

Quantum computing can potentially be applied to transform different industries like

Cryptography: Breaks classical encryption while enabling ultra-secure quantum encryption.

Healthcare: Accelerates drug discovery and personalized medicine.

AI & Machine Learning: Enhances optimization and data analysis.

Finance: Improves risk assessment and portfolio management.

Climate Science: Advances environmental modeling.

Innovation will be redefined by quantum computing, which will overcome obstacles to achieve previously unheard-of levels of speed, security, and efficiency. The future is quantum.

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Blockchain

This week in class we discussed about the Evolution, Features, Components, Types and Application of blockchain.

Blockchain technology is an advanced database mechanism that enables transparent and secure information sharing within a business network.

Evolution

First Generation: Introduced Bitcoin and digital currencies.

Second Generation: Added smart contracts for automated transactions.

Third Generation: Focuses on scalability, interoperability, and new applications.

Key Features

Decentralization: No central authority.

Immutability: Data cannot be altered.

Consensus: Transactions are validated via protocols like Power over work or Power over stake.

Key Components

Distributed Ledger: Shared, tamper-proof records.

Smart Contracts: Automated agreements.

Public Key Cryptography: Ensures security and authentication.

Types of Blockchain

Public: Open to all (e.g., Bitcoin, Ethereum).

Private: Restricted access for enterprises.

Consortium: Shared by multiple organizations.

Hybrid: Combines public and private features.

Applications

Payments & Money Transfers

Supply Chain Monitoring

Digital Identity Management

Secure Data Sharing

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AI, Machine Learning, Artificial Neural Networks.

This week we learnt about the above topic and my take home from it is that Artificial Intelligence (AI) enables machines to mimic human intelligence, driving innovations like speech recognition and recommendation systems. Machine Learning (ML), a subset of AI, allows computers to learn from data and improve over time.

Supervised vs. Unsupervised Learning are types of AI

Supervised Learning: Uses labeled data to train models for tasks like fraud detection and image recognition.

Unsupervised Learning: Finds patterns in unlabeled data, used for clustering and market analysis.

Artificial Neural Networks (ANNs)

ANNs mimic the human brain, processing data through interconnected layers

Input Layer: Receives raw data.

Hidden Layers: Extract features and process information.

Output Layer: Produces predictions.

Deep Learning, a subset of ML, uses deep ANNs for tasks like NLP and self-driving technology. As AI evolves, understanding these core concepts is key to leveraging its potential.

It was really quite enlightening.

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RFP Evaluation Criteria

This week in class we discussed about the above topic, and I was able to understand that RFP (Request for Proposal) evaluation criteria help organizations fairly and efficiently assess vendor proposals. Common criteria include technical expertise, cost, methodology, compliance, innovation, and overall fit.

We can evaluate proposals using simple lists, scoring matrices, or weighted scoring to prioritize important factors. Best practices include defining criteria early, maintaining consistency, and using scoring guides to ensure a fair and structured selection process.

By following these steps, organizations can choose the best vendor for their needs while maintaining transparency and efficiency.

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Business Gap

This week in class, I learned about various tools and frameworks used for gap analysis and decision-making:

SWOT Analysis: A tool for identifying internal Strengths and Weaknesses and external Opportunities and Threats. It helps in strategic planning by understanding the current state and potential challenges or advantages.

Fishbone Diagram: A visual tool for root cause analysis, used to identify potential causes of a problem. It organizes causes into categories like People, Process, Equipment, and Environment.

Cynefin Framework: A decision-making framework that categorizes situations into five domains (Simple, Complicated, Complex, Chaotic, and Disorder). It helps in determining appropriate actions based on the nature of the problem and its predictability.

Capability Maturity Model (CMM): A framework for assessing and improving process maturity. It consists of five levels (Initial, Managed, Defined, Quantitatively Managed, and Optimizing) and is commonly used in software development and organizational growth.

These tools provide structured approaches to identifying gaps, analyzing root causes, and guiding decision-making processes for better organizational outcomes.

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INTRODUCTION

Hello, my name is Augusta, and I'm an IT student who is fascinated about how technology is changing the world. I prefer exploring how innovation addresses real-life problems, and my areas of interest are artificial intelligence, cybersecurity, and cloud computing. The ability to analyze is my greatest asset, and in order to add to my theoretical understanding, I'm trying to get more hands-on experience. I know that emerging technologies refer to innovations that are in the early stages of development but have the potential to significantly impact industries and society. I'm eager to acquire knowledge about the uses, difficulties, and potential consequences of innovative technologies like quantum computing, AI, IoT and blockchain.