AI’s Got Brains and Business: Navigating the Smart Shift

In today’s edition…

• Why there’s no such AI glass-ceiling yet — Microsoft’s CTO explains

• Understand, create and implement your AI Copilot today

• Are job positions getting replaced soon by AI yet? — Google’s report digest

• The 3 key findings of how AI thinks and what does it means for your business — Anthropic report’s digest

AI tech leaders still releasing and announcing BIG. It’s our duty to keep you informed with what’s more relevant and applicable for your business. So let’s dive in.

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HOT THIS WEEK

Diminishing Returns? Not Even Close

Microsoft held the Build conference this past week and unveiled what could be one of the biggest announcements of the month, if not the year.

According to Microsoft’s CEO, Kevin Scott, we are not even close to diminishing returns with the power of AI models.

And the fact is that we touched on this topic in our latest newsletter edition and podcast. So go and check them if you haven’t done so yet.

That’s not even the whole of it. This accelerating pace of progress also comes with a massive drop in costs and gains in efficiency.

That’s the big picture of what’s coming. But what did Microsoft announce that’s applicable today?

Once again, a huge event with hundreds of announcements and new releases makes it overwhelmingly difficult to stay on top of everything.

And time is money, so here’s the distilled version of the most groundbreaking and applicable things that you should know.

💡 MUST KNOW: COPILOT STUDIO

The full event and keynotes were packed with outstanding announcements. But, if we have to choose, by far the main highlight goes to Microsoft Copilot Studio, that is now much more accessible and actionable for developers and businesses.

Among the updates, Copilot agents are now capable of managing complex, multi-step business processes with minimal human intervention.

This innovation allows for asynchronous task orchestration, memory and context utilization, and continuous learning and improvement, making AI a more proactive and intelligent collaborator in business processes.

This evolution signifies a significant leap in automation, transforming AI from a supportive role to an autonomous agent that can manage tasks across various functions such as IT, HR, and customer service.

💰 BUSINESS EDGE

You’ll get the most value on this section and if your dev team takes the time to go through the linked resources that we’ve curated, on each of the steps below.

Integration Strategy:

1. Identify Key Processes: Analyze business processes that can benefit from automation (e.g., IT support, HR onboarding, customer service). More detail on these examples here.
   

2. Pilot Implementation: Develop and deploy pilot projects using Copilot Studio to test the feasibility and performance of AI copilots in real-world scenarios.
   

3. Customization: Leverage the ability to create custom Copilot GPTs and plugins to tailor AI solutions to specific business needs.
   

4. Feedback and Iteration: Use the conversational analytics feature to gather insights and continuously improve AI performance based on user interactions and feedback.
   

5. Utilize Memory and Context Capabilities: Deploy AI that remembers past interactions to improve personalization and reduce repetitive queries.
   

6. Data Integration: Connect enterprise data through Copilot connectors for informed decision-making and personalized interactions.
   

7. Customization: Utilize Copilot Studio to create tailored solutions that align with specific business needs. (Tutorial in next section).

For more detail, watch and follow these steps on building your own Copilot tutorial.

Challenging Human Thought

Google's Gemini 1.5 aims to push the boundaries of the quantitative reasoning of AI by simulating the thought processes of mathematicians.

They show how this is achieved with Gemini 1.5 in their recent paper, when extending the reasoning inference time, significantly more intelligence from the same model size.

MEANING FOR BUSINESSES

For businesses, this means that models like Gemini 1.5’s will soon be able to fully embrace problem-solving and data analysis, in a much more powerful way than humans. This can save time and resources, allowing experts to focus on strategic decisions and innovation.

IMPACT ON JOBS

The Gemini 1.5 report highlights significant potential time savings in various industries.

As an example, the report mentions a 73% reduction in task time for photographers and 75% for programmers.

Despite the huge time saving potential of this, we believe it’s not there yet. The model's accuracy drops to around 70% when dealing with numerous details, so human oversight is needed that could lead minimal time savings or even leading to time-inefficiencies.

The report have many more amazing insights related to legal document analysis, medical research, codebase review and more, so be sure to check it out here.

Inside The Black Box: Understanding How AI Thinks

In a recent technical report, Anthropic Labs, made significant strides in understanding how large language models, like their Claude Sonnet model, process and represent information.

WHAT’S HAPPENING INSIDE

In a neural network, each neuron can contribute to multiple concepts, making it challenging to determine its specific role. Anthropic used a technique called dictionary learning to map out which neurons are responsible for which concepts.

PATTERN IDENTIFICATION

This exploration into the "monosemantics" of neural networks—essentially aimed to map individual neurons to specific, singular meanings.

For instance, certain neurons activate when the model processes programming errors, while others light up when it thinks about famous landmarks like the Golden Gate Bridge.

KEY FINDINGS

Anthropic's report highlights several key findings that underline the importance of their research:

• Code Mistakes: The model reliably identifies errors in various programming languages.

• Understanding Responses: It can discern when responses are insincere.

• Learning Abstractions: It can understand complex concepts, like the idea of a coding error, across different contexts.

Strategic Meaning for Businesses

Understanding these patterns will enhance the transparency, safety, and performance of AI models. Here’s why:

1. Trustworthy AI:

   • Your business will be able to build more transparent AI systems, fostering greater trust among users and stakeholders.

2. Safer AI:

   • Understanding neuron roles, such as the code error feature or the Golden Gate Bridge feature, can lead to the development of safer AI systems.

   • Your businesses will be able to ensure compliance with regulations and ethical standards by preventing models from generating harmful or biased outputs.

3. Smarter AI:

   • With a clearer understanding of how AI models process information, companies can fine-tune their systems for better performance and accuracy in AI applications.

CAVEMINDS STRATEGY CURATION

SLIDES AND TUTORIAL

Build your own copilot extensions

Microsoft Copilot ecosystem supports more than 50 plugins from major partners like Atlassian, Adobe, and ServiceNow, with thousands more planned to be integrated in the coming months.

This is a thought so that your team can experience a significant boost in productivity by automating tasks, generating content, and accessing data seamlessly across different platforms​ (Microsoft Learn)​​ (MS Cloud & Apps)​.

Check out the Copilot Extensions slides here, and click below to watch a full step-by-step tutorial on how to build your own extensions.

Key Use Cases:

1. Document Drafting in Word using MS Cloud & Apps.

2. Email Management in Outlook: Transforming long email conversations into short summaries and draft suggested replies (MS Cloud & Apps).

3. Data Analysis in Excel: Identifying trends and making data-driven decisions​ (MS Cloud & Apps)​.

4. Customer Service: Drafting proposals and project plans to grow the customer base​ (MS Cloud & Apps)​.

5. Meeting Management: Generating meeting ideas, organizing them into themes, creating designs, and summarizing whiteboard content during brainstorming sessions​ (Microsoft Learn)​.

💰️ BUSINESS EDGE

Build independent AI agents with Copilot Studio

Copilots can now act as independent agents triggered by events, providing personalized assistance in scenarios such as IT support, employee onboarding, and customer service.

You can find technical and detailed step-by-step on how to build a Copilot using Azure AI Studio here. We recommend you to share it with your dev team to start experimenting the wide range of possibilities and productivity enhancements. Check out all the Azure AI Studio capabilities here.

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• Practical Insights for Businesses: Unpacking breakthrough technologies by OpenAI and Google

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