There is a fair amount of discussion (and even some hand-wringing) around the idea of an LLM performance plateau. NLW leads a discussion inspired by https://www.bloomberg.com/opinion/articles/2024-11-20/ai-slowdown-is-everyone-else-s-opportunity

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Menlo Ventures' 2024 State of Enterprise AI Report reveals key insights into AI's transformative impact on businesses. From a 600% spending increase to a shift from pilots to production, this deep dive highlights enterprise adoption trends, the rise of in-house solutions, and the evolving role of AI agents. Discover how generative AI is reshaping every department, from IT to HR, and what this means for the future of business innovation.
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Could large language models (LLMs) continue improving after training? New innovations like test-time computing and self-evolving models suggest the possibility. OpenAI’s Orion and DeepSeek’s R1 light push reasoning boundaries, while Writer introduces "self-evolving" LLMs that learn in real time. This shift could redefine AI performance and enterprise adoption.
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A new study by IDC, commissioned by Microsoft, reveals generative AI delivers an average ROI of 370% in enterprise settings, with AI leaders achieving over 10x returns. Key findings show productivity use cases dominate current AI applications, but a shift toward revenue generation and industry-specific use cases is emerging. Despite these promising returns, lacking employee skills remains the top barrier to wider adoption.

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Ben Affleck’s perspective on AI and Hollywood sparks a thoughtful discussion on creativity and industry transformation. From writer and actor concerns about AI’s role in storytelling to studios embracing new possibilities, Affleck's comments balance optimism with caution. Explore insights on AI's potential to enhance creativity, reduce barriers to entry, and open new revenue streams while reshaping traditional roles in filmmaking.
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Anthropic’s AI outperforms OpenAI in a new AI research competition, sparking discussions about self-improving AI and its future implications. Meanwhile, Google’s Gemini leaps to the top of benchmarking charts, surpassing GPT-4 in multiple domains except coding. Also explored: Are AI benchmarks saturated, and how should businesses leverage existing capabilities during this period of incremental advancements?

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A reading and discussion inspired by https://a16z.com/rip-to-rpa-the-rise-of-intelligent-automation/

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Researchers at MIT share encouraging results around test-time training. NLW is joined by Google's NotebookLM to tell the story.

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OpenAI is set to release its autonomous agent "Operator" in January, a tool that aims to execute tasks like coding and booking autonomously, marking a potential breakthrough in AI's role in practical applications. Alongside this, OpenAI has unveiled an ambitious proposal to advance U.S. AI infrastructure, advocating for energy expansion and streamlined AI project approvals to maintain national competitiveness. This "Manhattan Project" for AI could reshape the future of tech and policy in the U.S.

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Explore the newly proposed Department of Government Efficiency (DOGE) and its potential to transform U.S. government operations with AI. Appointed by President-Elect Trump, Elon Musk and Vivek Ramaswamy are set to lead this agency, focusing on cutting government waste and increasing efficiency.

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Is AI development hitting a wall? Today’s episode explores reports that OpenAI’s Orion model, expected to surpass GPT-4, shows less impressive gains than anticipated. Researchers are now shifting focus to inference scaling, enhancing real-time reasoning rather than relying solely on traditional pre-training.

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