"For the majority of businesses, focus on building applications using agentic workflows rather than solely scaling traditional AI. That's where the greatest opportunity lies." - Andrew Ng, founder of DeepLearning.AI
LLMs no longer a novelty
Artificial intelligence is evolving rapidly. According to Microsoft CEO Satya Nadella, the standalone AI models are becoming commodities. This means the models themselves are plentiful and accessible. The real value is shifting away from just having a model to how businesses can use these capabilities to achieve specific outcomes.
Context is power
Nadella highlights a new competitive edge called context engineering. This involves connecting AI systems to actual business data and workflows. By grounding AI in an organization's specific information, it allows the technology to reason and plan effectively rather than just answering simple questions.
From Chats to Agents
The industry is moving beyond simple text prompts, and entering the era of agentic systems where AI can autonomously perform tasks across different applications. Tools like Copilot are acting as browsers for this new agentic web, handling complex actions like analyzing spreadsheets or assisting researchers. These advancements are reshaping how organizations operate. In the pharmaceutical sector, companies are exploring ways to speed up clinical trials. By integrating agents, they aim to bring essential medicines to the market much faster than traditional software development methods allowed in the past.
Fighting crime with technology
An example of this application is the new MahaCrimeOS AI platform. Launched in partnership with the Maharashtra government, this system helps police stations investigate cybercrime. It standardizes workflows and leverages generative AI to tackle evolving threats securely across over a thousand police stations.
Summary
Satya Nadella asserts that while AI models are becoming common, the future lies in context engineering and AI agents. Success now depends on grounding AI in enterprise data to create autonomous systems that solve real problems, from accelerating drug discovery to modernizing police investigations.
Food for thought
If AI agents can autonomously navigate workflows and make decisions, how will human accountability evolve when a software process makes a critical mistake?
AI concept to learn: Context engineering
This refers to the process of giving an AI model access to your specific documents, databases, and history so it understands the unique situation behind your request. Instead of giving generic answers, the AI uses this background information to provide highly relevant and accurate responses tailored to your actual business needs.
[The Billion Hopes Research Team shares the latest AI updates for learning and awareness. Various sources are used. All copyrights acknowledged. This is not a professional, financial, personal or medical advice. Please consult domain experts before making decisions. Feedback welcome!]
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