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#futureofai

3 posts3 participants1 post today
Kiara Taylor

TechDaily AI: The Latest Breakthroughs in Artificial Intelligence

Stay ahead of the curve with TechDaily AI! This podcast unpacks the latest AI innovations, industry trends, and real-world applications — from generative models and automation to ethics and future impacts. Perfect for anyone passionate about where artificial intelligence is headed next.

music.amazon.com/podcasts/e9ec

#AI#ArtificialIntelligence#TechTrends
Bluebash

Role of Large Action Models in Advancing Next-Gen AI Agents

LAM-based AI agents are leading a major leap in artificial intelligence by combining the power of decision-making with autonomous action execution. At Bluebash, we design smart, responsive agents built on LAM architecture to handle real-world operations with minimal human input. Our latest insights unpack how LAMs enable context-aware AI evolution that’s transforming industries.

🚀 Unlock the future of LAM-based intelligence → bluebash.co/blog/large-action-

#LAMbasedAI#AIagentsDevelopment#AIautomation
Hacker News

Small Language Models Are the Future of Agentic AI

arxiv.org/abs/2506.02153

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arXiv.orgSmall Language Models are the Future of Agentic AILarge language models (LLMs) are often praised for exhibiting near-human performance on a wide range of tasks and valued for their ability to hold a general conversation. The rise of agentic AI systems is, however, ushering in a mass of applications in which language models perform a small number of specialized tasks repetitively and with little variation. Here we lay out the position that small language models (SLMs) are sufficiently powerful, inherently more suitable, and necessarily more economical for many invocations in agentic systems, and are therefore the future of agentic AI. Our argumentation is grounded in the current level of capabilities exhibited by SLMs, the common architectures of agentic systems, and the economy of LM deployment. We further argue that in situations where general-purpose conversational abilities are essential, heterogeneous agentic systems (i.e., agents invoking multiple different models) are the natural choice. We discuss the potential barriers for the adoption of SLMs in agentic systems and outline a general LLM-to-SLM agent conversion algorithm. Our position, formulated as a value statement, highlights the significance of the operational and economic impact even a partial shift from LLMs to SLMs is to have on the AI agent industry. We aim to stimulate the discussion on the effective use of AI resources and hope to advance the efforts to lower the costs of AI of the present day. Calling for both contributions to and critique of our position, we commit to publishing all such correspondence at https://research.nvidia.com/labs/lpr/slm-agents.
#HackerNews#SmallLanguageModels#FutureOfAI
Kiara Taylor

Ever wondered how AI goes from training in the lab to making real-time decisions in your phone, car, or smart home? This episode demystifies AI inference—the process that brings machine learning models to life in practical applications. We break down how it works, why it matters, and where it's shaping the future of technology today.

#AI #MachineLearning #AIInference #SmartTech #TechExplained #FutureOfAI #AITech #TechPodcast

podcasts.apple.com/us/podcast/

What Is AI Inference? How Smart Tech Actually Works
Apple PodcastsWhat Is AI Inference? How Smart Tech Actually WorksPodcast Episode · TechDaily.ai · 06/24/2025 · 22m
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