The AI Year in Stories: Autumn 2024

December 30, 2024

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Customers can create such agents using several AI models developed in-house and by OpenAI for the agents.

We look at the articles that made the news in AI in 2024. Today, it is September, October, November's turn, with Microsoft AI Agents and IBM's new AI model

How Microsoft Intends to Democratise AI Agents

In a landscape where AI is evolving at breakneck speed, Microsoft has once again positioned itself at the forefront of innovation with an announcement on the next big iteration of AI: AI agents.

Due to premiere for the public in November, the new software described as "apps for an AI-driven world" can handle client queries, identify sales leads and manage inventory.

Available on its Copilot Studio, customers can create such agents using several AI models developed in-house and by OpenAI for the agents.

Examining the autonomous agents

Microsoft's CEO Satya Nadella and Jared Spataro, CMO of Copilot at Work, unveiled the company's latest AI offering at the AI Tour event in London.

Like Gen AI, autonomous agents represent a bold step in Microsoft's AI strategy, building upon the success of its Copilot platform, which has already amassed 2.1 million monthly users across its business applications.

These autonomous agents are custom-built AI applications designed to handle specific tasks for enterprise workers, autonomously.

By automating routine functions, Microsoft aims to free up employees' time, allowing them to focus on more strategic and creative endeavours. This development is not just another incremental improvement; it's a paradigm shift in how businesses interact with AI.

In the UK, retailer Pets at Home has harnessed these agents to minimise time-consuming tasks such as data entry and client proposal processing.

This level of accessibility could lead to widespread adoption across various industries, potentially transforming entire sectors overnight. It aligns with the growing trend of 'agentic AI', which refers to AI systems that possess a degree of autonomy and can act on their own to achieve specific goals.

Microsoft has incorporated safeguards into the system, allowing workers to intervene and check the agent's work. This human-in-the-loop approach aims to strike a balance between automation and oversight, crucial for maintaining trust in AI systems.

IBM Releases Smaller, Faster & Open Source Granite AI Models

The release marks a shift in the enterprise AI market, where most providers charge for access to their models.

Global technology firms are expanding their enterprise AI offerings as corporate demand increases for business applications. IBM has launched its latest enterprise AI models under an open source licence.

The release marks a shift in the enterprise AI market, where most providers charge for access to their models. IBM’s Granite 3.0 family encompasses three model types designed for business use, which it says are smaller, faster and significantly cheaper – with IBM finding its new models are between three and 24 times cheaper than large frontier models in early proofs of concept.

Model architecture and capabilities

The Granite 3.0 family encompasses three model types released under the Apache 2.0 licence. The general purpose language models, available in 8B and 2B versions, handle text generation, classification and summarisation tasks. These models support Retrieval Augmented Generation (RAG), a technique that enables AI systems to incorporate external data sources.

The safety models, called Granite Guardian, establish ethical parameters across 19 safety benchmarks, including social bias, toxicity and hallucination detection. IBM reports these models demonstrate higher accuracy in harm detection compared to Meta's Llama Guard models.

The mixture-of-experts models enable deployment for low latency applications and CPU-based systems., while IBM says its new time series model claims performance surpassing models 10 times larger from competitors including Google and Alibaba.