AI Today Podcast: Looking ahead at AI (and AI Today) in 2024
Dec 27, 2023
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The podcast discusses the growing presence of Generative AI, its integration into everyday objects, and the importance of predictability in AI models and fully autonomous vehicles. It also emphasizes the significance of project management in AI projects, explores the differences between RPA and Generative AI, and highlights the impact of Generative AI on the industry in 2024.
Generative AI is being embedded in everyday products like spreadsheets and word documents, making it more accessible and widely used.
There are challenges and trade-offs associated with generative AI, including concerns about over-embedding, hallucinations, bias, and misinformation.
Open source language models are gaining traction and may replace closed models, offering greater flexibility and customization without reliance on expensive API calls.
Deep dives
Generative AI Continues to Expand and Embed Itself in Various Applications
Generative AI was a significant trend in 2023, and its impact is expected to continue in 2024. Generative AI has become more accessible and is being used in various applications. It is now being embedded in everyday products like spreadsheets and word documents. The ease of embedding generative AI capabilities has led to its widespread adoption. However, there are concerns about the potential negative effects of generative AI, such as hallucinations, bias, and the spread of misinformation. Organizations and individuals need to be cautious while embracing generative AI in order to mitigate these issues.
The Challenges and Promise of Generative AI in 2024
While generative AI offers exciting possibilities, it also presents challenges and trade-offs. On the positive side, generative AI has the potential to enhance human capabilities and augment intelligence. However, there are concerns about over-embedding generative AI in everyday objects and the potential for it to replace common sense. Moreover, generative AI systems may exhibit issues such as hallucinations, bias, and confidently providing incorrect information. These challenges need to be addressed to ensure the trustworthy and responsible use of generative AI.
The Rise of Open Source Language Models and the Shift from Closed Models
Open source language models have gained significant traction in the AI landscape. These models, such as Mistral and LAMA, offer greater flexibility and accessibility compared to closed models like those provided by specific vendors. The trend suggests that open source models might replace closed models, as they enable easier embedding and customization without reliance on expensive API calls. As open source models become more popular, the closed models might face challenges in adaptability and compliance with regulations. The availability of open source models is expected to drive a shift in the marketplace.
The Changing Perception of AI and the Need for Trustworthy AI
The perception of AI has shifted from overwhelming enthusiasm to a more neutral and cautious attitude. As generative AI becomes more prevalent, issues of trust and responsible use have emerged. The potential for false information, fake news, and increasing regulation have raised concerns about the trustworthiness and reliability of AI systems. Trustworthy AI has become a significant focus, with an emphasis on ensuring that AI systems provide accurate and reliable results. The changing perception of AI and the need for trustworthy AI will shape the AI landscape in 2024.
The Impact on Jobs and the Growing Importance of Project Management
As AI becomes more widespread, the demand for prompt engineers, specialists in generating effective AI prompts, is expected to increase. Prompt engineers will play a crucial role in implementing and managing generative AI projects. The rise of generative AI also highlights the importance of project management in AI initiatives. Project managers will play a critical role in ensuring the success of AI projects and managing expectations. Additionally, the automation space, such as RPA, is experiencing a cooling trend in venture capital investments, with limited new use cases emerging. The emphasis has shifted towards project management and the successful implementation of AI solutions.
In this episode of the AI Today podcast we want to look at some of the biggest trends in AI, including where AI is headed in 2024 and what this means for you.
Generative AI Gets Embedded in Everything
The ease and availability of Generative AI makes it easy to embed in everything.