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This week we see two big content players give the green light to their workers to utilise AI: Fiverr, the gig-economy platform and The New York Times. This is what we expect to be the beginning of a seismic shift in the way AI is used in jobs. Not in replacing people, but rather in freeing them up to spend more time on the complicated and interesting parts of their work.

In today’s deep dive, we cover the differences between LLMs and GPTs, Agents and AI. If you’ve started to take an interest in AI (and we hope if you’re reading this, then you have!), it’s likely these terms have come up in your reading. Our guide will set you out to understand which to use and when…

In today’s Brief:

• Musk Launches Powerful AI Model Challenging ChatGPT Rivals 🤖

• Fiverr Empowers Gig Workers with Personalised AI tools 🚀

• Mistral Emerges as European AI Powerhouse Contender 🇫🇷

Today’s Feature:

Unravelling AI: Understanding the Basic Terms 🌪️

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Musk Launches Powerful AI Model Challenging ChatGPT Rivals 🤖

The Brief: Elon Musk's xAI launches Grok 3, a powerful AI model built with massive computing power, offering advanced reasoning and research capabilities for X Premium subscribers.

Details:

• Elon Musk's xAI releases Grok 3, claiming it outperforms GPT-4o on benchmarks and offers advanced reasoning capabilities.

• Grok 3 is a family of models with features like DeepSearch, reasoning modes, and internet research capabilities.

• X Premium+ subscribers will first access Grok 3, with a new $30 monthly SuperGrok plan offering additional features.

• Musk plans to open source Grok 2 in the coming months and continues to pursue a more politically neutral AI model.

Why It Matters:

Musk's xAI is aggressively challenging big tech's AI dominance through Grok 3, offering advanced capabilities, competitive performance, and a potential disruptive approach to AI development that prioritises transparency and truth-seeking.

Fiverr Empowers Gig Workers with Personalised AI tools 🚀

The Brief: Fiverr launches AI tools enabling freelancers to create personalised AI models from their work, offering new revenue streams and empowering gig workers to adapt to technological disruption.

Details:

• Fiverr introduces a "Personal AI Creation Model" allowing freelancers to train AI on their work and charge for its use.

• The platform aims to help gig workers remain competitive by providing AI tools that generate content based on their unique style.

• Freelancers can access a Personal AI Assistant for customer service, with the ability to customise and control AI interactions.

• Fiverr plans to offer top-performing contractors company shares, though specific details of the share allocation remain undisclosed.

Why It Matters:

Fiverr is transforming gig work by enabling freelancers to monetise their expertise through personalised AI models, offering a proactive strategy for workers to adapt to technological disruption while maintaining control of their professional identity.

NYT Launches Strategic AI Tools for Editorial Workflow 🤖

The Brief: The New York Times strategically integrates AI tools for product and editorial teams, setting clear guidelines for responsible usage while maintaining editorial integrity and innovation.

Details:

• The New York Times has approved AI tools for its product and editorial teams, including potential use in social copy and SEO headlines.

• The publication launched an internal AI summary tool called Echo and provided guidelines for staff on responsible AI tool usage.

• Editorial staff can use AI for suggesting edits, brainstorming interview questions, and research, but cannot draft or significantly revise articles.

• The announcement comes amid an ongoing lawsuit against OpenAI and Microsoft for alleged copyright infringement in AI training.

Why It Matters:

As traditional media adapts to AI, the New York Times demonstrates a strategic, controlled approach to technological integration, balancing innovation with journalistic integrity while potentially reshaping content creation and distribution processes.

Unravelling AI: Understanding the Basic Terms 🌪️

Behind every AI breakthrough lies a set of fundamental concepts. Understanding these basics will help you make smarter decisions about implementing AI in your job, business or personal life.

The AI Family Tree

Artificial Intelligence (AI) serves as an umbrella term for systems designed to mimic human intelligence. Think of it as a family tree, with various branches representing different capabilities and approaches. Machine Learning forms the trunk of this tree - it's the foundation that allows systems to learn from data without explicit programming. Deep Learning, a more sophisticated branch, uses complex neural networks to process vast amounts of information, enabling more advanced capabilities.

Types of AI Systems

Today's AI landscape features Artificial Narrow Intelligence (ANI) - systems excellent at specific tasks but limited to their training. Your spam filter, chatbots, and image recognition software are all examples of ANI. Artificial General Intelligence (AGI) represents the next frontier - systems that could match human-level intelligence across various tasks. While we're not there yet, many companies are working towards this goal. Beyond that lies Artificial Super Intelligence (ASI), a theoretical stage where AI would surpass human intelligence in virtually every field.

Modern AI Tools Explained

Let's break down today's AI tools through the lens of a new office assistant:

Large Language Models (LLMs) form the foundation - they're like having access to a vast knowledge base. (E.g., ChatGPT…) Think of them as incredibly well-read individuals who can process and generate human-like text.

GPTs (not to be confused with OpenAI’s ChatGPT specifically!) are like day-one assistants who understand their general role. They can engage in conversations and help with various tasks, but they might need guidance on company-specific procedures.

Agents are more like seasoned assistants who understand their specific role and have access to additional tools. They can use calendars, databases, or other software to complete tasks more effectively.

Different Flavours of Generative (“Gen”) AI

Language models excel at understanding and generating text, from writing reports to analysing documents. Image generation tools like DALL-E, Midjourney, and Stable Diffusion can create, edit, and modify visual content based on text descriptions. Video generation, while newer, allows for the creation of simple animations and video content, though with varying degrees of quality.

Major Players in AI

The AI landscape features several prominent models, each with unique strengths:

• OpenAI's GPT models offer versatile capabilities across various tasks.

• Anthropic's Claude excels at detailed analysis and maintaining longer conversations.

• Google's Gemini shows promise in multimodal tasks, handling text, images, and code.

• Meta's LLaMA focuses on open-source development.

• Mistral (the main European model, from France) specialises in efficient, smaller models.

• Perplexity stands out for real-time information access.

• DeepSeek (China’s leaders) offers strong coding capabilities.

• Grok (from Musk’s X) aims to provide more personality in interactions.

Making AI Work for You

The key to getting the most from these AI tools lies in effective prompting. Our WISER framework provides a structured approach to crafting prompts that get better results. Good prompting is like giving clear instructions to an employee - the more specific and well-structured your request, the better the outcome.

Understanding Tokens and Context

When working with AI models, you'll encounter terms like 'tokens' and 'context window'.

Tokens are the units of text that AI models process - roughly one token equals 3/4 of a word.

The context window represents how much information the model can consider at once. Think of this as akin to a new assistant’s short-term memory: they can only remember so much in one go. Yet no matter how much they forget about what you’ve just told them, they will still be able to recall the name of their first pet. Larger context windows mean the AI can handle longer conversations and documents more effectively. Even with smaller context windows, the model won’t forget it’s prior training however.

The AI landscape continues to evolve rapidly, but these fundamental concepts remain crucial for understanding and implementing AI in your business. Whether you're looking to automate customer service, generate content, or analyse data, knowing these basics helps you choose the right tools for your needs.

Want to learn more about implementing these technologies in your business? Check out our previous articles on practical AI applications and our article to the WISER^TM AI prompting framework.

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