Making the Most of AI and GPT-like Models: An examination of the industries most suitable for integration

Paulina Lewandowska

19 Jan 2023
Making the Most of AI and GPT-like Models: An examination of the industries most suitable for integration

Introduction

The way businesses work is being revolutionized by artificial intelligence (AI) and language models like GPT. AI is quickly becoming a crucial tool for businesses wanting to stay competitive in today's fast-paced economy, from automating monotonous processes to offering insightful analysis and predictions. In this article, we'll look at how companies are using GPT-like models and AI to boost productivity, boost efficiency, and boost revenue. We will look at the numerous uses of AI in the corporate world, from customer service to financial analysis. We'll also look at how GPT-like models are specifically employed in content generation and natural language processing to scale up communication and human-computer interaction.

AI implementation by sector

AI and models like GPT can be particularly beneficial in a variety of sectors, including but not limited to:

SectorApplications
Natural Language Processing (NLP)Language Translation, Text Summarization, Question Answering
Content CreationAutomated written content generation (news articles, product descriptions, social media posts)
BusinessAutomating tasks (customer service, sales, marketing), Financial forecasting and analysis
HealthcareMedical Diagnosis, Drug Discovery, Personalized Medicine
EducationPersonalized learning experience, Grading and providing feedback
Transport and logisticsSelf-driving cars, Supply chain management
RoboticsObject recognition, Navigation, Manipulation
GamingRealistic and engaging gameplay, New types of games

GPT-like Models in NLP and Content Creation: Automating Writing and Personalizing Content

GPT-like models have demonstrated substantial skills in the areas of Natural Language Processing (NLP) and content generation. Language translation, text summarization, and question answering are just a few of the natural language processing activities that are catered to by language models like GPT-3.

Automated writing is one of the most well-liked uses of GPT-like models in NLP and content generation. GPT-3 is capable of producing written content such as blog entries, product descriptions, and social media updates automatically. By automating the process of content production, GPT-3 can save enterprises a significant amount of time and resources because it can produce cohesive and grammatically sound text. This makes GPT-3 perfect for jobs like writing reports, email drafts, and chatbot scripts for customer assistance.

GPT-like models have uses in personalized content creation for clients in addition to automated authoring. By evaluating consumer data and creating content that is specific to the user's interests and preferences, GPT-3, for instance, can be used to provide personalized product suggestions or targeted advertising. This might aid companies in enhancing their marketing initiatives and raising client involvement.

Automation: Using AI to Simplify Business Processes 

Automating processes is one of the most obvious ways that organizations are utilizing AI. AI can handle a wide range of monotonous activities, from customer care chatbots to automated financial analysis, freeing up employees to concentrate on more worthwhile work. Simple customer care requests, like responding to frequently asked queries, can be handled by AI-powered chatbots, while more sophisticated systems can even manage complicated problems. Additionally, financial analysis tasks like fraud detection and trend prediction can be automated using machine learning models.

AI-Assist in Healthcare Revolution: Diagnosis and Treatment 

AI is being applied in a variety of ways in the healthcare sector to improve efficiency and precision. AI-powered systems, for instance, can help clinicians diagnose illnesses by reviewing medical images and making recommendations. This raises diagnostic precision while lowering the possibility of human error. Drug development is another area where AI is being used in healthcare. AI is capable of analyzing enormous amounts of data, including genetic data, to find potential novel treatments and medications. AI is also being used to develop individualized treatment regimens for patients, which take into consideration aspects like medical history, genetics, and other personal traits.

Intelligent tutoring and Personalized Learning with AI in Education 

Similar to how it is being used in business, AI is being used in education to help teachers grade assignments and give feedback to students. Based on a student's skills, shortcomings, and preferred learning style, AI is used to generate customised learning plans for them. Additionally, it contributes to the development of intelligent tutoring programs that support teachers by offering tailored feedback and assistance to students both within and outside of the classroom. AI is also being used to automate grading and assessment, which can assist save teachers time and increase the effectiveness of the educational system.

AI-Optimized Logistics and Transportation: Supply Chain Management to Self-Driving Cars 

AI is also being used by the transportation and logistics sector to boost productivity and cut expenses. The development of self-driving automobiles is one example of how AI can be used to enhance road safety and lower the frequency of accidents brought on by human mistake. Another area where AI may be used to optimize is supply chain management. This is done by forecasting demand, analyzing data, and making better decisions. AI can also improve fleet management by tracking the whereabouts and condition of vehicles, anticipating maintenance requirements, and increasing productivity.

Enhancing Capabilities and Real-world Functionality of AI-Powered Robotics 

AI is being applied in the field of robotics to enhance the capabilities and usefulness of robots. Robots are now able to recognize and interact with items in the real world thanks to AI, for instance in the field of object recognition. Another area where AI is applied to help robots autonomously navigate in challenging settings is navigation. AI can also be utilized to enhance the manipulation abilities of robots, allowing them to carry out a larger variety of activities, like grabbing and manipulating real-world objects. Robots are improving their ability to work in real-world settings and do tasks that were previously insurmountable thanks to the incorporation of AI.

From Realistic Gameplay to Game Development: AI in the Gaming Industry 

AI is also employed in the video game industry to build new game genres and more realistic and captivating gameplay. By offering more lifelike AI-controlled characters and environments, game AI is one application of AI that aims to improve gameplay realism and engagement.

AI can also be applied to the creation of new game mechanisms and game genres, such as games that adjust to the preferences and skill level of the player. AI can speed up the process of finding and fixing flaws in games, giving gamers a better gaming experience. Game testing can also be improved by AI. We may anticipate even more advancements in the application of AI to gaming as it continues to develop, pushing the limits of what is feasible in the gaming sector.

Conclusion

In conclusion, the incorporation of AI and models resembling the GPT into numerous industries and businesses is proving to be quite advantageous. These technologies are transforming how we conduct business, improve medical diagnosis in healthcare, personalize education, optimize logistics and transportation, and even transform the gaming sector. GPT-like models have enormous potential for content creation and natural language processing. Businesses should be aware of the advantages and potential of these technologies. The integration of AI and GPT-like models in several industries has a promising future.

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Blockchain for Creators: Secure and Sustainable Infrastructure

Miłosz Mach

07 Nov 2025
Blockchain for Creators: Secure and Sustainable Infrastructure

In today’s digital creative space, where the lines between art and technology are constantly blurring, projects like MARMALADE mark the beginning of a new era - one where creators can protect their work and maintain ownership through blockchain technology.

For Nextrope, being part of MARMALADE goes far beyond implementing features like screenshot blocking or digital watermarking. It’s about building trust infrastructure - systems that empower creators to thrive in the digital world safely and sustainably.

A new kind of blockchain challenge

Cultural and educational projects come with a completely different set of challenges than typical DeFi systems. Here, the focus isn’t on returns or complex smart contracts - it’s on people: artists, illustrators, educators.

That’s why our biggest task was to design secure yet intuitive infrastructure - lightweight, energy-efficient, and accessible for non-technical users exploring Web3 for the first time.

“Our mission wasn’t to build another financial protocol. It was to create a layer of trust for digital creators.”
— Nextrope Team

Security that stays invisible

The best security is the kind you don’t notice.
Within MARMALADE, we focused on making creators' protection seamless:

  • Screenshot blocking safeguards artworks viewed in browsers.
  • Dynamic watermarking helps identify unauthorized copies.
  • Blockchain registry ensures every proof of ownership remains transparent and immutable

“Creators shouldn’t have to think about encryption or private keys - our job is to make security invisible.”

Sustainability by design

MARMALADE also answers a bigger question - how to innovate responsibly.
Nextrope’s infrastructure relies on low-emission blockchain networks and modular architecture that can easily be adapted for other creative or cultural initiatives.

This means the technology built here can support not only artists but also institutions, universities, and educators seeking to integrate blockchain in meaningful ways.

Beyond technology

For Nextrope, MARMALADE is more than a project — it’s proof that blockchain can empower culture and creators, not just finance. By building tools for digital artists, we’re helping them protect their creativity and discover how technology can amplify human expression.

Plasma blockchain. Architecture, Key Features & Why It Matters

Miłosz Mach

21 Oct 2025
Plasma blockchain. Architecture, Key Features & Why It Matters

What is Plasma?

Plasma is a Layer-1 blockchain built specifically for stablecoin infrastructure combining Bitcoin-level security with EVM compatibility and ultra-low fees for stablecoin transfers.

Why Plasma Blockchain Was Created?

Existing blockchains (Ethereum, L2s, etc.) weren’t originally designed around stablecoin payments at scale. As stablecoins grow, issues like congestion, gas cost, latency, and interoperability become constraints. Plasma addresses these by being purpose-built for stablecoin transfers, offering features not found elsewhere.

  • Zero-fee transfers (especially for USDT)
  • Custom gas tokens (separate from XPL, to reduce friction)
  • Trust-minimized Bitcoin bridge (to allow BTC collateral use)
  • Full EVM compatibility smart contracts can work with minimal modifications

Plasma’s Architecture & Core Mechanisms

EVM Compatibility + Smart Contracts

Developers familiar with Ethereum tooling (Solidity, Hardhat, etc.) can deploy contracts on Plasma with limited changes making it easy to port existing dApps or DeFi, similar to other EVM-compatible infrastructures discussed in the article „The Ultimate Web3 Backend Guide: Supercharge dApps with APIs".

Gas Model & Token Mechanism

Instead of forcing users always to hold XPL for gas, Plasma supports custom gas tokens. For stablecoin-native flows (e.g. USDT transfers), there is often zero fee usage, lowering UX friction.

Bitcoin Bridge & Collateral

Plasma supports a Bitcoin bridge that lets BTC become collateral inside smart contracts (like pBTC). This bridges the security of Bitcoin with DeFi use cases within Plasma.
This makes Plasma a “Bitcoin-secured blockchain for stablecoins".

Security & Finality

Plasma emphasizes finality and security, tuned to payment workloads. Its consensus and architecture aim for strong protection against reorgs and double spends while maintaining high throughput.
The network launched mainnet beta holding over $2B in stablecoin liquidity shortly after opening.

Plasma Blockchain vs Alternatives: What Makes It Stand Out?

FeaturePlasma (XPL)Other L1 / L2
Stablecoin native designusually second-class
Zero fees for stablecoin transfersrare, or subsidized
BTC bridge (collateral)only some chains
EVM compatibilityyes in many, but with trade-offs
High liquidity early✅ (>$2B TVL)many chains struggle to bootstrap

These distinctions make Plasma especially compelling for institutions, stablecoin issuers, and DeFi innovators looking for scalable, low-cost, secure payments infrastructure.

Use Cases: What You Can Build with Plasma Blockchain

  • Stablecoin native vaults / money markets
  • Payment rails & cross-border settlement
  • Treasury and cash management flows
  • Bridged BTC-backed stablecoin services
  • DeFi primitives (DEX, staking, yield aggregation) optimized for stablecoins

If you’re building any product reliant on stablecoin transfers or needing strong collateral backing from BTC, Plasma offers a compelling infrastructure foundation.

Get Started with Plasma Blockchain: Key Steps & Considerations

  1. Smart contract migration: assess if existing contracts can port with minimal changes.
  2. Gas token planning: decide whether to use USDT, separate gas tokens, or hybrid models.
  3. Security & audit: focus on bridge logic, reentrancy, oracle risks.
  4. Liquidity onboarding & market making: bootstrap stablecoin liquidity, incentives.
  5. Regulation & compliance: stablecoin issuance may attract legal scrutiny.
  6. Deploy MVP & scale: iterate fast, measure gas, slippage, UX, security.