Understanding the Stages of Artificial Intelligence: ANI, AGI, and ASI

Artificial Intelligence (AI) is rapidly transforming our world, but not all AI is created equal. As shown in the image above, AI development can be categorized into three main stages: ANI, AGI, and ASI. Let’s break down what each stage means and how they differ.

ANI: Artificial Narrow Intelligence
ANI, or Artificial Narrow Intelligence, refers to AI systems that are designed for a specific task. These systems excel at what they do, but they cannot perform tasks outside their programmed domain. Examples include chess-playing computers and voice assistants. ANI is the type of AI most commonly used today, powering everything from recommendation algorithms to smart home devices.

AGI: Artificial General Intelligence
AGI stands for Artificial General Intelligence. This stage represents AI that can understand, learn, and apply knowledge across a wide range of tasks-essentially matching human-level intelligence. AGI would be able to reason, solve problems, and adapt to new situations just like a person. While AGI is a popular topic in science fiction and research, it has not yet been achieved.

ASI: Artificial Superintelligence
ASI, or Artificial Superintelligence, is the hypothetical stage where AI surpasses human intelligence in every aspect-creativity, problem-solving, decision-making, and more. ASI would be “superhuman,” possessing abilities far beyond our own. This stage remains speculative, but it sparks important discussions about the future of AI and its potential impact on society.

⭐❓Quick Quiz❓⭐

True or False?

  1. AGI refers to artificial intelligence that matches or exceeds human intelligence across most domains.
  2. ASI stands for Artificial Super Intelligence and is expected to be far beyond human capabilities.
  3. AGI is the stage of AI that is narrow and task-specific, such as voice assistants or chess programs.

 

Answers

  1. True
  2. True
  3. False: this is ANI
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AI Replaces Human Workforce

Quick Summary

An Indian e-commerce company, Dukaan, has radically replaced 90% of its workforce with AI chatbots, signalling a potentially transformative workplace trend.

Key Points

  • Suumit Shah, Dukaan’s CEO, implemented complete AI automation
  • Initial performance metrics appear positive after twelve months
  • Experiment highlights critical tension between technological efficiency and human employment

Why It Matters

This case study reveals profound technological and societal risks, including potential mass unemployment, reduced human interaction quality, and fundamental shifts in labour dynamics that could dramatically reshape professional ecosystems.

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You Are Not Prompting ChatGPT Correctly: How to Get Consistent, Branded Images

Want to generate a set of professional, matching images with ChatGPT? The secret is using a structured prompt and only changing the details that matter to you. Here’s a step-by-step guide-no technical skills needed!

Step 1: Copy the Prompt Template

Use the following prompt as your starting point. It’s designed to give you a futuristic trading card look, but you can adapt it for any branded image:

{"prompt": 
	"A futuristic trading card with a dark, moody neon aesthetic and soft sci-fi lighting. The card features a semi-transparent, rounded rectangle with slightly muted glowing edges, appearing as if made of holographic glass. At the center is a large glowing logo of {{logo}}, with no additional text or label, illuminated with a smooth gradient of {{colors}}, but not overly bright. The reflections on the card surface should be subtle, with a slight glossy finish catching ambient light. The background is a dark carbon fiber texture or deep gradient with soft ambient glows bleeding into the edges. Add subtle light rays streaming down diagonally from the top, giving the scene a soft cinematic glow. Apply light motion blur to the edges and reflections to give the scene a sense of depth and energy, as if it's part of a high-end tech animation still. Below the card, include realistic floor reflections that mirror the neon edges and logo—slightly diffused for a grounded, futuristic look. Text elements are minimal and softly lit: top-left shows '{{ticker}}', top-right has a stylized signature, and the bottom displays '{{company_name}}' with a serial number '{{card_number}}', a revenue badge reading '{{revenue}}', and the year '{{year}}'. Typography should have a faint glow with slight blurring, and all elements should feel premium, elegant, and softly illuminated—like a high-end cyberpunk collectible card.",
	"style": {"lighting": "Neon glow, soft reflections","font": "Modern sans-serif, clean and minimal","layout": "Centered, structured like a digital collectible card","materials": "Glass, holographic plastic, glowing metal edges"},
"parameters": {
"logo": "INGAGE logo (attached)","ticker": "ING","company_name": "The INGAGE Institute","card_number": "#0512","revenue": "€96.5B","year": "2025","colors": ["blue", "white", "dark gray"]},"medium": "3D render, high-resolution digital art","size": "1080px by 1080px"
}

You can notice that you don’t need to start with “Create an image” 😉


Step 2: Personalize the Details

Replace the parts in brackets with your own information:

  • [your logo]: e.g., “INGAGE logo” or “your company logo”
  • [your brand colors]: e.g., “blue, white, silver”
  • [your ticker]: e.g., “ING”
  • [your company name]: e.g., “The INGAGE Institute”
  • [your card number]: e.g., “#0512”
  • [your revenue]: e.g., “$96.5B”
  • [your year]: e.g., “2025”

Step 3: Keep the Structure, Change Only the Details

For a series of images (like cards for different products or team members), keep the rest of the prompt the same and update only the details above. This ensures all your images have the same style and layout.

Step 4: Generate and Download

Paste your personalized prompt into ChatGPT’s image generator. If you want to use your own logo, upload it as an attachment when prompted. Download your finished image and use it wherever you need cohesive branding.

Step 5: Repeat for a Consistent Set

Want a whole deck or series? Just repeat these steps, changing only the details each time. Your visuals will stay consistent and professional.

Tips

  • For custom logos, upload your image and mention it in your prompt (e.g., “Framer logo (attached image)”).
  • Try the same approach for other image types-just adjust the description to fit your needs.

With this method, anyone can create a cohesive set of branded images using ChatGPT-no design skills required!

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Only hire if AI can’t do it.

Quick Summary

Shopify’s CEO Tobi Lütke mandates compulsory AI integration across all company operations, signalling a radical approach to technological adaptation.

Key Points

  • All employees must incorporate AI into workflows
  • Teams must demonstrate AI’s capability before requesting additional resources
  • Leadership expects employees to reimagine work processes with AI agents

Why It Matters

This strategic directive represents a critical inflection point in organisational technological adoption, potentially creating significant competitive advantages while simultaneously introducing complex implementation risks around workforce readiness, technological dependency, and potential skill misalignment.

Read more…

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Have you insured your robot?

Quick Summary

South Korea legalises robotic public space movement, enabling 14 companies to test outdoor robot deployments.

Key Points

  • 14 companies currently testing outdoor robot technologies
  • Robots permitted for tasks like delivery and security
  • Represents significant regulatory breakthrough for robotics

Why It Matters

This development introduces unprecedented risks around technological integration, public safety, liability frameworks, and potential insurance complexities associated with autonomous robotic systems interacting in shared environments.

Read more…

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AI beats doctors

Quick Summary

Swiss researchers develop AI diagnostic tools that outperform traditional tuberculosis detection methods

Key Points

  • AI echography tool achieves 93% sensitivity and 81% specificity
  • Swaasa Al platform detects tuberculosis via cough analysis with 86% accuracy
  • Smartphone-based diagnostics enable healthcare in remote regions

Why It Matters

These innovations could dramatically reduce healthcare barriers by providing rapid, cost-effective diagnostic capabilities in low-resource environments, potentially saving lives through early detection and minimising complex testing requirements.

Read more… (in French)

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Flights with Zero Emissions?

Quick Summary

Airbus unveils ZEROe hydrogen aircraft, targeting zero-emission aviation by 2035.

Key Points

  • Four 2-megawatt electric motors
  • Zero carbon emissions, only water vapour released
  • Developed with 220+ global partners

Why It Matters

This transformative concept represents a critical pivot in aviation’s environmental strategy, potentially disrupting traditional fuel models and presenting significant challenges in hydrogen infrastructure, production scalability, and technological reliability. The success of ZEROe could dramatically reshape carbon-neutral transportation and create new risk assessment frameworks for aerospace insurers.

Read more…

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Don’t be polite!

Quick Summary

Saying please and thank you to AI chatbots generates unexpected environmental costs.

Key Points

  • Polite interactions with AI consume millions in electricity
  • 67% of Americans are courteous to chatbots
  • AI data centres use around 2% global electricity

Why It Matters

The seemingly innocuous practice of being polite to AI represents a hidden environmental burden, demonstrating how small digital interactions can collectively contribute to significant carbon emissions. As AI technology becomes more prevalent, understanding and mitigating its energy consumption becomes crucial for sustainable technological development.

Read more…

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When AI Fakes Reality

Quick Summary

OpenAI’s new reasoning models demonstrate unprecedented levels of AI hallucination, raising serious reliability concerns.

Key Points

  • o3 and o4-mini models show hallucination rates of 33% and 48% respectively
  • Internal and independent evaluations confirm significant model inaccuracies
  • OpenAI acknowledges limited understanding of hallucination causes

Why It Matters

These elevated hallucination rates pose substantial risks, potentially compromising decision-making processes, generating false information, and undermining the credibility of AI technologies across critical sectors. The inability to predict or control these inaccuracies suggests profound challenges in current AI development approaches.

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Zero-Human Factories

Quick Summary

Xiaomi’s autonomous factory produces smartphones without human intervention

Key Points

  • Operates 24/7 with zero employees
  • Produces one phone per second (31 million annually)
  • Utilises advanced AI-driven platform for production optimisation
  • Can operate entirely in the dark – no light is needed. The factory’s machines and AI systems do not require illumination

Why It Matters

This technological breakthrough signals a profound shift in manufacturing, potentially disrupting traditional labour models, requiring substantial capital investment, and creating complex risk scenarios around technological dependency, supply chain resilience, and workforce transformation. The automation represents a significant technological leap with far-reaching economic and social implications.

Watch the Original video.

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AI systems are grown, not built

Generative AI’s inherent opacity creates profound challenges in understanding and managing potential technological risks.

Dario Amodei, co-founder and CEO of Anthropic and former Vice President of Research at OpenAI, highlights these issues in his influential work on the urgency of interpretability.

Key Points

    • AI systems are grown, not built, making their internal mechanisms unpredictable
    • Emergent behaviors make risk assessment difficult
    • Opacity prevents comprehensive understanding of potential AI capabilities and limitations

Why It Matters

The lack of transparency in AI models introduces significant uncertainties that could lead to unintended consequences, including potential misuse in sensitive domains like financial assessment, cybersecurity, and scientific research. Without clear interpretability, organisations cannot definitively establish comprehensive risk management strategies, potentially exposing themselves to unprecedented technological vulnerabilities.

Read Dario’s post.

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AI, build or buy?

Quick Summary

AI Development Trends show companies pivoting from custom solutions to commercial AI tools

Key Points

  • Gartner reports AI project failure rates over 50% higher for inexperienced companies
  • Vendor-driven market emerging with pre-built AI functionalities
  • Focus shifting to incremental improvements rather than massive AI transformations

Why It Matters

The AI landscape is rapidly evolving, presenting significant risks for organisations investing in complex, in-house AI development. Companies without deep technological expertise face higher chances of project failure, potentially wasting substantial financial and human resources. The emerging trend suggests a more pragmatic approach: leveraging commercially available AI tools with proven functionality and lower implementation risk. This shift requires strategic reassessment of AI investment strategies, focusing on targeted, achievable improvements rather than ambitious, potentially unsustainable projects.

Read more on cio.com.

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