AI's 2024 Outlook: Insights from Germanidis, Hooker, Liang, Luccioni, Moiloa, and Scott - Blockchain.News
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AI's 2024 Outlook: Insights from Germanidis, Hooker, Liang, Luccioni, Moiloa, and Scott

Batch Issue 229 envisions AI's 2024 vision, emphasizing inclusive, transparent, and ethical development, focusing on multimodal models, real-time interactivity, language gap, transparency, governance, and human contributions.


  • Jan 02, 2024 12:46
AI's 2024 Outlook: Insights from Germanidis, Hooker, Liang, Luccioni, Moiloa, and Scott

An interesting look into the predicted breakthroughs in artificial intelligence for the year 2024 is provided by the Batch Issue 229, which included contributions by Anastasis Germanidis, Sara Hooker, Percy Liang, Sasha Luccioni, Pelonomi Moiloa, and Kevin Scott.

The growth of artificial intelligence systems is something that Anastasis Germanidis anticipates, especially in the areas of video creation and real-time interaction. He places an emphasis on the automation of AI research and the building of modular systems. Sara Hooker forecasts that there will be an increased emphasis on inclusiveness, along with developments in multimodal and multilingual models, as well as a trend toward smaller and more efficient AI models. In her speech, she emphasizes the significance of tackling the language gap in artificial intelligence and supporting a wider worldwide engagement in research pertaining to AI.

Concerns are raised by Percy Liang on the decreasing openness in artificial intelligence (AI), and he emphasizes the need of rigorous assessments and governance, including the implementation of the Foundation Model openness Index at the same time. He advocates for more democratic methods in value alignment and model building, and he places a strong emphasis on the role of assessment in artificial intelligence technologies.

A greater appreciation of human creativity and labor in the creation of artificial intelligence is something that Sasha Luccioni is advocating for. She also emphasizes the ethical issues that surround training data and the development process. She is an advocate for artificial intelligence systems that are more human-centric and transparent procedures.

In order to overcome the issues that arise when deploying artificial intelligence in environments with limited resources, Pelonomi Moiloa is concentrating on the creation of AI models that are more compact, more effective, and use less data. She places an emphasis on the potential of artificial intelligence to solve global concerns and argues for AI that is more accessible and helpful to a variety of groups to include.

Kevin Scott contemplates the fast development of artificial intelligence as well as the possibility of contemporary generative AI. In order to get the most of the capabilities of artificial intelligence tools, he stresses the need of keeping up with the latest advances and experimenting with new tools.

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