Elena' s AI Blog

AI

Artificial intelligence (AI) refers to systems that learn, reason, and act with increasing autonomy. On this site, the AI tag covers practical developments in models, tools, infrastructure, and real-world constraints — from coding agents and local experimentation to cloud security, power limits, and the economics shaping how AI is built and used.

AI’s New Defaults and Hidden Costs


This week’s AI signals were less about one dramatic model launch and more about AI becoming infrastructure. GPT-5.5 Instant became the default model many ChatGPT users will meet first. Google shipped practical developer updates for multimodal retrieval, webhooks, and faster Gemma inference. Microsoft added automated right-sizing for AI-heavy SQL workloads. DeepMind and CCP framed EVE Online as a living lab for long-horizon agents. The EU’s Digital Omnibus pushed AI governance toward concrete implementation timelines. CAISI expanded pre-release frontier model testing. A Chinese court signalled that AI adoption alone does not justify dismissal. And data centres became a ratepayer and permitting fight.

Capability Meets Constraint


This week's AI signals mark a sharper turning point: frontier capability kept rising, while multimodal enterprise launches and cybersecurity controls moved into production. OpenAI expanded GPT-5.5, DeepSeek released V4, NVIDIA announced Nemotron 3 Nano Omni, IBM released Granite 4.1, and Anthropic launched Claude Security public beta.

Codex CLI Part 4: Advanced Operations, Troubleshooting, and Team Patterns


Part 4 closes the Codex CLI series with advanced operational patterns: non-interactive automation, permission strategy, troubleshooting playbooks, and team-level standards for reliable adoption.

Has the open-source gap closed?


OpenAI ended the week by releasing GPT-5.5 — codenamed Spud — retaking the top spot across 14 benchmarks and positioning itself explicitly as an agent runtime rather than a chat model. Two Chinese labs shipped frontier-quality models on the same day: Alibaba's Qwen 3.6-Max-Preview closed its weights for the first time, and Moonshot's open-source Kimi K2.6 reached #4 on the global intelligence index, level with Western frontier labs. OpenAI's gpt-image-2 introduced reasoning into image generation. Google confirmed Gemini will power the next Siri. Amazon committed another $25 billion to Anthropic. And the Stanford AI Index documented a field accelerating faster than every institution surrounding it. Nine signals. A week that moved the map.

Codex CLI Part 3: Practical Workflows for Blogging and Python Development


A practical, high-depth guide to using Codex CLI for blog editing and Python delivery: review loops, safe refactoring, debugging, and non-interactive automation with explicit guardrails.

Agents, Cyber Models, and the Safety Stack Tightening Up


This week's clearest AI signal was not a giant new general model. It was the rapid convergence of stronger agent tooling, more cyber-capable systems, and tighter safety controls. Anthropic shipped Claude Opus 4.7 with new cyber safeguards. OpenAI expanded trusted cyber access, upgraded its Agents SDK, and pushed Codex deeper into real developer workflows. Microsoft launched a cheaper production-grade image model. Meanwhile, Anthropic's Mythos triggered a real regulatory response across central banks and governments.

AI Signals: Controlled Releases and Platform Integration


This week’s AI signals point to a shift toward controlled releases and platform integration. Meta launched Muse Spark, Microsoft expanded its multimodal stack, and efficiency improvements continue to shape deployment. Instead of rapid disruption, the focus is on deliberate progress and clearer strategic direction.

AI Signals: From Models to the Full Stack


This week’s AI signals show a clear shift from models to the full stack. Microsoft expanded its multimodal model lineup, AI is being used to design chips, and new AI-native devices are emerging. At the same time, a powerful Anthropic model remains unreleased due to safety concerns, trust is lagging behind adoption, and startup valuations are accelerating again.

The Digital Butler or Trojan Horse? A Privacy Playbook for Persistent AI Agents


Persistent AI agents can save hours each week, but they also turn hidden prompt injections into real-world actions unless you design strict controls. This guide shows how to harden agent workflows with policy gates, isolation, scoped permissions, and safe auditing.

AI's New Bottleneck


The week, AI signals shifted attention from generic model chatter to concrete releases and constraints. Google launched Gemini 3.1 Flash Live and Lyria 3 Pro for developers, while reports of Anthropic's unreleased Mythos/Capybara model highlighted high-capability safety pressure. At the same time, U.S. datacenter policy and GitHub's Copilot data-default change reinforced that governance and infrastructure are now product-critical.

Infrastructure Is the New Frontier


This week’s biggest AI signal was not a new frontier model. It was the fast consolidation of infrastructure, distribution, and cost. Nvidia pushed agentic AI and robotics as stack problems. Anthropic invested in enterprise distribution and tested asynchronous delegation. Microsoft, Mistral, and OpenAI advanced the efficiency tier. Xiaomi and Rakuten showed how global and contested the open-weight race has become.

Edge AI in Everyday Operations


Practical ways businesses can use Edge AI to make faster, local decisions without replacing existing systems or relying on constant cloud connectivity.

Better Models, Burnout, and a $599 Mac


GPT-5.4 arrived with native computer use and a 1M-token context window. Anthropic moved further toward becoming an enterprise platform. And Block's layoffs, alongside new HBR research on "AI brain fry," made one thing clear: this week's real signal was not just better models, but what AI is doing to work.

AI Is Splitting Into Tiers


Three fast, cheap models landed in the same week — Gemini 3.1 Flash-Lite, GPT-5.3 Instant, and Qwen3.5-9B. That is not a coincidence. The cost-performance frontier just moved.

Vibe Coding Wasn't Enough — The Lightweight System I Use to Turn AI Prompts into Deployed Apps


Vibe coding can generate working apps in minutes — but most don’t last. I replaced chaotic prompting with a simple, spec-driven AI workflow that turns ideas into reliable, deployed tools.

72.5%, $710B, and a March in London


This week's signals trace a collision between software and reality: Anthropic's leap in computer automation, a record-breaking $710B cloud capex plan, and the resulting shockwaves in consumer electronics prices and global energy policy.

OpenClaw Isn't a Chatbot Anymore. It's Infrastructure.


AI agents like OpenClaw are wonderful tools — but without strict access rules and proper supervision, they can turn an ordinary Tuesday into something you will be explaining to HR for weeks. In this post, we explore the very real risks of deploying AI assistants carelessly, from leaked credentials to messages you absolutely did not mean to send. Most importantly, we look at how to use OpenClaw the right way, because when deployed thoughtfully, it is one of the most exciting and capable tools we are only just beginning to understand.

Agentic AI at Scale: New models, $30B, and the UKRI Strategy


Weekly AI Signals for February 12-19, 2026: Claude Sonnet 4.6, Gemini 3.1 Pro, Anthropic's $30B Series G, and UKRI's £1.6 billion AI strategy show how capability, capital, and sovereignty are shaping AI at scale.

AI Improves Itself While We Argue About Permits


This week's signals show AI capability racing ahead while real-world constraints tighten: $2.5B inference funding, self-improving models from OpenAI and Anthropic, ByteDance's restricted video AI, and data centres stuck in permit battles. The gap between what models can do and what infrastructure can support is becoming the central story.

Codex CLI Part 2 — Security Controls & Safe Editing


Learn how Codex CLI balances permissions and approvals to keep you in control. Master essential commands like /diff and /review, understand the three security modes, and make your first safe code edits with full visibility.

The AI Paradox: Lightning Fast and Gridlocked


This week's signals were about constraints and acceleration at once: AI-assisted cloud attacks, multi-year grid queues in Europe, new infrastructure funds, and consumer GPU pricing pressures — alongside fast adoption of consumer AI apps.

Protecting Infrastructure in an Era of AI-Assisted Attacks


Short 1–2 sentence summary.

Using AI Code Assistants Safely


A practical, human guide to using generative code assistants safely — without leaking secrets, breaking trust, or losing control of your work.

Chips, Capex, and Code Risk


This week’s AI signals were practical rather than flashy: Microsoft’s earnings tied AI to long-term capex, Anthropic pushed export-focused regulation, China approved limited H200 imports, and everyday compute continued to rise. Together, they point to AI becoming infrastructure — budgeted, regulated, and increasingly constrained.

This Week in AI: Regulation Heat, Cloud Bets, and Agentic Shopping


A structured breakdown of this week's AI signals: PwC reveals only 12% of CEOs get AI ROI, Meta faces a child-safety trial, chip export oversight advances, and Google's UCP proposes agentic commerce standards.

Getting Started with Codex CLI


Learn what Codex CLI is, how to install it on Mac, Linux, and Windows, and take your first steps with this AI coding assistant that runs in your terminal.

The Week AI Got Practical: Laws, Power, and Open Models


A structured breakdown of the week's AI signals: state-level safety laws harden, Texas becomes an AI infrastructure node, and Google advances agentic commerce rails.

My Multi-Agent Workflow


A structured guide to building a calm, dependable multi-agent publishing workflow: which AI tool operates at which layer, and how to wire them together without chaos.

Signals from the AI Supply Chain


A structured breakdown of this week's AI signals: TSMC confirms AI chip demand is structural, Apple partners with Google Gemini to power Siri, and Google introduces the Universal Commerce Protocol for agentic shopping.

AI's Week of Limits: Safety, Control, and Real-World Physics


A structured breakdown of the week's AI signals: France chooses Mistral for sovereign AI, Nvidia pivots to inference at CES, Grok exposes the deployment safety gap, and fusion labs show where AI earns real trust.

As 2025 Closes: AI's Week of Regulation, Infrastructure, and Autonomy


A structured breakdown of the final week of 2025: China's emotional AI regulations, the SoftBank–DigitalBridge $4B infrastructure deal, and Meta's $2B+ acquisition of autonomous agent startup Manus.

Hardware Handshakes, Prompt Injection Reality, and AI Beyond the Screen


A structured breakdown of the final week of 2025: the $20B Nvidia–Groq deal, OpenAI's prompt injection admission, the CONTEXT.md best practice, and Waymo's Gemini deployment.

AI Interfaces, Safety, and Multimodal Systems


A structured breakdown of this week's AI signals: Google's Gemini 3 Flash raises the bar for speed, A2UI lets agents build their own interfaces, and OpenAI/Anthropic add structural safety for younger users.

Antigravity 1.11.9 vs Cursor 2.1.42 (Universal): A Practical Comparison


A structured head-to-head comparison of Antigravity 1.11.9 and Cursor 2.1.42 — two IDEs with opposing philosophies: outcome delegation vs conversational assistance.

Labs, Law and New Hardware Horizons


A structured breakdown of this week's AI signals: DeepMind's automated lab, OpenAI's screenless hardware, and why 42 attorneys general are demanding strict LLM safeguards.

A Short Tale of Bravery (at the Dentist)


A personal story about facing the drill, followed by an AI Dentistry Evolution Matrix detailing how AI and robotics are quietly becoming the dentist's ultimate co-pilot.

AGI Timelines, 3D Vision, and the Reality of AI Scams


A structured breakdown of the week's AI signals: from DeepMind's 2030 AGI forecast and Meta's SAM3D breakthrough to the chilling reality of voice-cloning scams.

A Journey Through AI and Code


Another year has passed, and Elena's AI Blog is now four years old! Join me as I reflect on the year we shifted from generative AI to agentic orchestration, and outline the strategic roadmap for 2026.

The New Skill Stack, from Writing Code to Managing Intelligence


The era of the bricklayer is over; the era of the architect has begun. A structured guide to the new Developer Skill Stack, from writing agent contracts to tracking AI energy costs.

Claude Opus, ChatGPT Shopping, EV Forecasting and DeepSeekMath-V2


A structured breakdown of this week’s most meaningful AI shifts—from Claude Opus 4.5's coding enhancements to ChatGPT shopping agents, and DeepSeek's open-source mathematical breakthroughs.

Ethics, Gravity, and the Future We're Actually Building


Google's Antigravity IDE killed the text editor in favour of agent orchestration, while the WHO demanded humanity 'hold the pen.' Explore the architectural shifts of Gemini 3 and why the AI Wild West is officially over.

Ethics, Code, Chips, and a Petaflop on Your Desk


A structured breakdown of the week's AI workflow shifts: from NVIDIA's desktop petaflop and MIT's LLM modularity to why 91% of developers still insist on reviewing AI-generated code.

Could AI Become a New Religion?


A gentle exploration of how institutions move from resisting scientific novelty to shaping AI ethics. We examine the theological limits of artificial intelligence and why kindness and human dignity must guide the future we build.

Apache-Licensed Summarizers


Looking for summarisation models you can safely use in your app? Here is a definitive guide to Apache-licensed transformer models, complete with selection matrices and production gotchas.

AI Weekly — Agents Grow Up, Clouds Get Bigger


OpenAI books a mountain of AWS compute, Google ships production tooling for agents, and GitHub adds org-wide steering. A structured breakdown of the week's AI workflow shifts.

A few thoughts on Cursor 2.0


Cursor 2.0 shifts from autocomplete to autonomous agents via the Composer model and Sandboxed Terminal. Evaluate if this IDE migration is right for your workflow with our Decision Matrix.

AI Infrastructure, Small Models, and Multi-Agent Coding


NVIDIA pushes exaflop limits, IBM releases lightweight edge models, and GitHub networks AI coding agents. A structured breakdown of the week's hardware and workflow shifts.

Quantum Thinking, Light Models, Living Networks


Google achieves quantum leaps, researchers build 1.7M parameter 3D models, and telecom networks self-optimise. A structured breakdown of the week's critical AI infrastructure shifts.

LoRA fine-tuning wins


You no longer need to retrain entire language models. LoRA allows you to teach new capabilities via tiny adapters. Here is the architectural code, deployment cheat sheets, and production pitfalls.

AI Honesty, Agents, and the Fight for Truth


California mandates AI transparency, Microsoft pushes agents to the OS level, and publishers fight for source attribution. A structured breakdown of the week's critical AI policy shifts.

Safety, Agents, and Compute


Three major AI announcements dropped this week that demand architectural attention. Google taught agents to use computers visually. DeepMind built an agent that automatically patches vulnerabilities. OpenAI secured 6 gigawatts of compute capacity. Here is the technical delta and how builders must adapt.

Cursor Made Me Do It


AI makes software development feel frictionless, leading to unprecedented feature bloat. We explore the symptoms of AI scope creep and define a strict architectural framework to maintain control.

AI Got Rules, Wheels & a Lab Coat


AI just got new safety rules, Europe is steering into autonomous roads, and MIT taught models some physics. Busy week.

AI’s Busy Week


From Britain’s sovereign AI push to coding models that think like engineers, this week’s breakthroughs show AI growing brains, memory, and initiative — plus some long-overdue policy wins.

Gemini CLI versus Claude CLI


Command-line AI tools are the new pocket knives of coding life. We compare Gemini CLI and Claude CLI, detailing their installation, privacy profiles, SWE-bench accuracy, and how to integrate them via Python.

AI this week


ChatGPT goes mainstream with 700M weekly users, Google finds a cure for hallucinations, GPT-5 Codex rewrites your code, textbooks finally get personal, and AR learns when to keep quiet.

Vibe Coding with Cursor AI


Testing Cursor AI in Agent Mode feels like coding with a slightly eccentric but eager partner. Friendly, fast, sometimes forgetful — here’s how GPT-5, Auto mode, and grok-code-fast stack up, with real specs.

AI weekly news


This week in AI: leaner models beating the giants, Google rewriting the speed–accuracy trade-off, AI that codes for scientists, smarter DNA design, and OpenAI trying to tame the AI job market.

AI weekly


We have picked up new AI happenings this week: GRPO for smarter training, reasoning models that cut the nonsense, entry-level jobs under pressure, Nano Banana stealing the image crown, and GPT-5 hacks unlocking hidden power.

How to Create a Weekly Menu with ChatGPT-5


This week, I let ChatGPT-5 into my kitchen. The result? A complete weekly meal plan for two people, tailored macros, batch-cooking flows, fridge-friendly PDFs, and even a laminated checklist with tick boxes.

AI weekly wins


This week, AI became cheaper, more natural, and a lot more practical. Oxford’s new optimiser slashes training bills by 80%, OpenAI’s voice system talks like a real human, and Google’s ‘Nano Banana’ image model quietly outshines the big players. Somewhere between a notebook for AI memory and hybrid reasoning for everyone, the field is shifting from expensive experiments to everyday tools.

Who Did the AI Learn From?


Large Language Models learn similarly to Rembrandt's apprentices — by endlessly studying the masters. Yet, modern AI models hide their sources. We explore the legal and ethical necessity of a structured transparency framework for AI training data.

This week in AI


This week’s AI breakthroughs make the technology feel less like distant research and more like practical tools. From open-source giants and real-time voice recognition to edge creativity, workplace automation, and smarter data reasoning — here are five updates worth your attention.

This week in AI


From Europe’s multilingual AI surge to Google’s ultra-efficient Gemma model, Meta’s self-supervised vision leap, and new tools reshaping AI safety and testing — here are the top AI developments this week.

Workflow Automation with n8n


Manual content pipelines inevitably fail at scale. After outgrowing brittle Python cron jobs, I migrated my infrastructure to n8n—a self-hosted, node-based orchestration layer. Here is the technical breakdown of configuring databases, managing OAuth2 security, and deploying AI-driven agents.

Will SaaS Survive?


SaaS isn't dying—it's evolving. AI is disrupting traditional workflows and pricing models, but innovative companies are adapting by becoming infrastructure layers, owning domain expertise, and focusing on outcomes rather than interfaces.

This week in AI


This week in AI saw groundbreaking releases from industry giants. OpenAI unveiled GPT-5 along with open-source GPT-OS-120b and 20b, making high-end AI accessible from laptops to phones. Google introduced DeepPolisher for genome error correction and Genie 3 for creating interactive virtual worlds. Alibaba launched GSPO powering Qwen3, plus Qwen-Image for free text-to-image generation. Anthropic rolled out Persona Vectors for consistent AI personalities. New mobile-ready AI models and coding assistants rounded out a week that made AI faster, more open, and more integrated into everyday tech.

Self-critical AI


Can Large Language Models achieve meta-cognition regarding their own stylistic patterns? In this primary research experiment, I tested Gemini, ChatGPT, and Claude to see if they could not only replicate my human writing style, but actively self-correct when confronted with AI-detection tools like Grammarly.

Vibe coding with Generative AI


I've been getting into "vibe coding" recently, quickly prototyping some of my ideas, and working on my pet projects. I must confess that the AI-assisted coding is a very addictive activity, and must be taken with caution since it has some security implications and requires a careful prompts engineering.

How to Use Claude AI


What is Claude AI? What can we do with it, and how? Let's explore this fantastic AI assistant by Anthropic.

How CustomGPT Mitigates AI Hallucinations


CustomGPT reduces AI errors using specialised knowledge, quality data, and user feedback. Along with RAG, it provides accurate and reliable content for various applications.

Is DeepSeek R1 Secure?


There is a big question about DeepSeek's security (and also the security of any software product, in fact), safety, and legal usage outside of China. I am sharing my opinion and some relevant links on this topic.

DeepSeek R1 With Ollama


This post explores the use of Ollama, a state-of-the-art language modelling framework, in conjunction with pre-trained models such as DeepSeek R1.

AI in 2024


As 2025 approaches, let's reflect on 2024's key AI advancements, including specialized models, growth in AI creativity, and the introduction of the AI Act. Here are my thoughts on the notable events.

Multimodal AI


Multimodal AI is rapidly evolving, pushing the boundaries of what machines can understand and achieve by combining information from multiple modalities like text, images, audio, and video. This post explores the core techniques of realising multimodal AI, existing systems and related research.

Celebrate Halloween with AI


Halloween, celebrated on October 31, has its roots in ancient Celtic rituals. Halloween allows us to unleash our creativity by crafting spooky costumes and decorations. In this post, I will suggest several ways to celebrate Halloween with the help of AI. AI can provide eerie sound effects, assist in costume design, offer voice modification features, and present fun filters for your face. Enjoy the celebration!

What is RAG? How Retrieval-Augmented Generation actually works


Large language models are impressive, but they suffer from a major flaw they hallucinate facts because they are essentially just predicting the next word. Retrieval-Augmented Generation (RAG) fixes this by grounding the AI in verified data before it answers. Here is an overview of how it works and the current state of research.

Narrow AI, General AI, Superintelligence, and The Real Intelligence


I discuss the main AI types in this post. I share my understanding of the possibility of general intelligence in the future.

ARC-AGI benchmark and a hefty prize


I am sharing information about the recent Kaggle competition launch, which focuses on advancing general intelligence.

Sending Emails with Python and receiving your messages


Running a static site on GitHub Pages means I don't have a backend to process forms or send newsletters. But that hasn't stopped me. Here is how I handle incoming messages, and how I use Python and Gmail to send automated emails.

Can AI hallucinate?


AI hallucinations are a critical phenomenon in AI, referring to instances where AI systems generate inaccurate or nonsensical information. This post explores the main causes of AI hallucinations, their implications, possible benefits, and existing solutions.

To cite or perish


Proper citation is a must to maintain academic and ethical integrity. It is a valuable skill that promotes respect for other people, creates a chain of arguments paramount in research and science, and protects one's life efforts in the future. Herein, I write my approach to citation. This might be useful for my student readers.

Robots and True Love


In this post, I write about robots and their creation challenges in real-life tasks, research areas, safety and ethical considerations, and future aspirations. I also briefly refer to a few starting points for creating robots with Raspberry Pi and Python.

Virtual Presenters (AI Avatars in-depth)


Digital humans are taking over training modules and marketing videos, and the technology is surprisingly accessible. Here is a look at my favourite platforms for creating AI avatars, plus a quick guide to generating your own in Python.

Super-girls don't cry in face-swaps


I wanted to see myself flying over Niagara Falls as a superhero. Here is how I did it — InsightFace Bot, Midjourney, and a Python/OpenCV implementation with Haar cascades and seamless blending.

Podcast: How can we build trust and safety around AI?


Lawyer Cláudia Lima Costa is an expert in Artificial Intelligence and has created an amazing podcast that raises pertinent questions about trust and safety in AI systems. I was fortunate enough to be invited to a relaxed discussion where I shared my views on various topics related to AI, such as AI evolution, AI applications, data sources for training models, copyright, data protection, privacy-preserving techniques, and achieving reliable, explainable, safe, and helpful AI.

Explainable AI is possible


The complexity of AI, particularly deep learning models, has led to the "black box" criticism, highlighting the lack of understanding about how deep learning models arrive at their decisions. While there's truth to this concern, having a nuanced view is important. In this post, I share my view on AI explainability, that it is complex, however possible.

OpenAI's Model Show-off


OpenAI's GPT models are highly sophisticated machine learning models that are used in various fields such as natural language processing, coding assistance, and content creation. OpenAI's newest video-generating model, Sora, sets a new benchmark in video generation technology, which I quickly explore in this post.

chatGPT and Friends


ChatGPT is a powerful language model that has revolutionised the way we interact with technology. This post explores ChatGPT and its alternatives, delving into their capabilities, applications, and ethical considerations.

AI Synthesised Voices


In this post, I discuss voice synthesis and cloning, and mention fantastic AI tools and APIs for creating high-quality human-like voices from text or for automatic voice dubbing.

Living with AI in Pursuit of Happiness


This blog is not about coding or AI; it is about living with AI in human society, striving for happiness and building on technological advances.

Blog Writing with AI in MindStudio


BlogGenie created a draft of this post at YouAI (MindStudio) and aims to demonstrate how AI writing assistants can streamline the blog generation process. It focuses specifically on leveraging YouAI for overall framing and BlogGenie for on-page SEO best practices. This allows for creating initial drafts in seconds rather than hours. You still have to edit and correct an outline to finalise your post.

Creating Websites with AI on Mixo.io


Have you ever wished for a website that writes itself? This dream is now a reality thanks to the advancement in Artificial Intelligence (AI). With Mixo.io, you can create stunning websites using AI technology--in minutes! In this blog post, we will explore website creation with Mixo.io.

Machine-Learning Process


The machine learning process involves a series of steps and activities designed to develop and deploy machine learning models to solve specific problems or make predictions. To simplify, we create programs that take in data and produce desired results in machine learning. There are several stages in the machine-learning process that we briefly describe in this post.

Why AI will never void humanity?


Why AI will never void humanity? What AI wants badly? I was thinking about these questions while travelling. I will share my initial thoughts with you, my dear reader.

Generate Music with AI


In this post, we will get into music generation with AI. We will briefly explore existing AI applications generating audio. We will explore transformer usage while coding music generation with HuggingFace transformers in Python.

A Warm August and Vacation


In this post, I write about what's happening in my life. August 2023 is quite warm, and I have decided to have a short vacation, which is much needed since I am preparing a surprise for you, my dear reader.

AI-Free Website Design


In this post, I write about my efforts in creating CSS and HTML pages for my website with chatGPT and why I ended up doing it myself while learning from the bot, Google Search, CodePen and w3schools.

GPT Implications for Coding


The AI evolution has implications for programming and programmer jobs. GPT usage allows for quicker product releases and a focus on user requirements. However, low-coding jobs could be delegated to AI, new skills for AI-assisted programming be required or access to sophisticated models only available to some. The new coding age is upon us. In this blog post, I highlight the opportunities and challenges of AI-assisted code generation and share my experiences using chatGPT.

Mastering Midjourney Prompts for Stunning Images


In this post, I write about creating stunning designs in Midjourney. We create AI-generated designs for an ice cream cafe. In the end, I list all prompts and handy keywords to take away for your fantastic own creations.

The Magic of AI Tools


In this post, I list some of my favorite AI applications for productivity and fun.

The Remarkable Evolution and Milestones of AI


In this post, I outline the AI evolution and its most prominent milestones with chatGPT and Midjourney.

From Dutch Golden Age to AI Art: A Journey with Vermeer and AI


In this post, I collaborated with ChatGPT to explore the captivating World of Dutch art and Johannes Vermeer. As an art critic and historian, ChatGPT provides fascinating insights into Vermeer's masterpieces and the historical events that influenced them. I also share my emotional experience of visiting a Vermeer art exhibition, and we'll have some fun creating AI art with Jasper.ai, DALL-E, Stable Diffusion Playground and Midjourney bot. Take advantage of my tips for refining ChatGPT's output and the prompts I used to get the best results. Join me on this adventure and discover the beauty of Dutch art and AI-art outcomes!

The Most Useful AI-Content and Plagiarism Detection Tools


With the development of AI-content generators such as chatGPT, we have a new need to identify such content, and the tools of AI-content detection are currently being developed. Writing assistants and plagiarism detection tools also include AI-content detection. In this post, I talk about the most visible AI tools that help us mitigate plagiarism and motivate us to create original and well-written content. Indeed, I will start with the definition of plagiarism, why it's terrible, and move quickly into helpful tools in AI-content and plagiarism detection that are available today.

Machine Learning Tests using the Titanic dataset


In this post, we created and evaluated several machine-learning models using the Titanic Dataset. We have compared the performance of the Logistic Regression, Decision Tree and Random Forest from Python's library scikit-learn and a Neural Network created with TensorFlow. The Random Forest Performed the best!

Python coding with chatGPT


In this post, I did some Python coding with chatGPT. We have coded a neuron, a simple neural network, and learned how to train it. I am pleased with the result. I think that chatGPT has excellent potential for CS students and all coders that want to update their skills effectively. Is it an end of the StackOverflow? We cannot see the feature. However, we still need social interaction with humans, and AI cannot substitute human communication.

Happy New Year!


My best wishes for 2023! I wish you happiness, health, and excellent luck in the New Year! Let your best wishes come true, and your professional goals are achieved with success!

chatGPT Wrote me a Christmas Poem


In this post, I shared my thoughts on chatGPT, its technology, and its possible societal implications. I also asked it to write a Christmas poem for me, which was pretty good!

TensorFlow: Transfer Learning (Feature Extraction) in Image Classification


Image classification is a complex task. However, we can approach the problem while reusing state-of-the-art pre-trained models. Using previously learned patterns from other models is named "Transfer Learning." This way, we can efficiently apply well-tested models, potentially leading to excellent performance.

Artificial Neural Networks


Artificial neural networks (ANNs) are the cornerstone of Deep Learning algorithms. The name and the architecture are adopted from the human brain's neural network. ANNs are designed to simulate human reasoning based on how neurons communicate. ANNs contain a set of artificial neurons connected.

Deep Learning vs Machine Learning


Artificial Intelligence (AI) is a field of computer science. AI provides methods and algorithms to mimic human intelligence, reasoning, and decision-making and provide insights, which businesses could use in research or industry to build new exciting and innovative products or services. Machine Learning (ML) is a subset of AI with algorithms that learn from data. In this post, we sort out the differences between AI and ML.