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SpaceXAI has launched Grok 4.5, moving its 1.5-trillion-parameter V9 model out of private beta and into public availability. The company describes it as its smartest model yet, built for coding, agentic tasks, and knowledge work, and notably trained alongside the coding tool Cursor. The launch follows a July 8 post from Elon Musk saying the model would go public after strong beta feedback, pitching it as an Opus-class model that is faster, more token-efficient, and cheaper. It arrives […]

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Optimistic Training and Convergence of Q-Learning — Extended Version

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In recent work it is shown that Q-learning with linear function approximation is stable, in the sense of bounded parameter estimates, under the $(varepsilon,κ)$-tamed Gibbs policy; $κ$ is inverse temperature, and $varepsilon>0$ is introduced for additional exploration. Under these assumptions it also follows that there is a solution to the projected Bellman equation (PBE). Left open is uniqueness of the solution, and criteria for convergence outside of the standard tabular or linear MDP settings. The present work extends […]

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Machine Learning System Design -The Model Serving Triangle, With One Forward Pass Flowing Through Every Trade-off (Part3)

Machine Learning System Design -The Model Serving Triangle, With One Forward Pass Flowing Through Every Trade-off (Part3)

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Author(s): Utkarsh Mittal Originally published on Towards AI. The Model Serving Triangle, With One Forward Pass Flowing Through Every Trade-off (Part3) Part 1-p https://pub.towardsai.net/the-ml-system-design-interview-with-numbers-flowing-through-every-stage-part-1-a77888339297?source=friends_link&sk=9064640f37c84a131ef24b1126bc0cf9 Three pieces of memory math that every candidate must have memorizedThis article discusses the complexities and trade-offs of machine learning model serving, detailing how decisions revolve around three sources: latency, throughput, and cost. It emphasizes the importance of understanding these factors when deploying models in production and features practical examples and strategies to maintain […]

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Perception Is All You Need: A Neuroscience Framework for Low Cost Sensorless Gaze in HRI

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arXiv:2604.09829v1 Announce Type: new Abstract: Gaze-following in child-robot interaction improves attention, recall, and learning, but requires expensive platforms ($30,000+), sensors, algorithms, and raises privacy concerns. We propose a framework that avoids sensors and computation entirely, instead relying on the human visual system’s assumption of convexity to produce perceptual gaze-following between a robot and its viewer. Specifically, we motivate sub-dollar cardboard robot design that directly implements the brain’s own gaze computation pipeline in reverse, making the viewer’s perceptual system […]

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GPU Training for 14b Models

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I’m a researcher and for my research I’m training a 14B-parameter model. However my available compute resources are limited to a single NVIDIA H100 GPU with 95 GB of VRAM provided by my institution via SSH. How do you all manage situations like this when working with large models? Please share your thoughts and experiences. submitted by /u/StatusArrival3382 [link] [comments]

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Tool-MCoT: Tool Augmented Multimodal Chain-of-Thought for Content Safety Moderation

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arXiv:2604.06205v1 Announce Type: new Abstract: The growth of online platforms and user content requires strong content moderation systems that can handle complex inputs from various media types. While large language models (LLMs) are effective, their high computational cost and latency present significant challenges for scalable deployment. To address this, we introduce Tool-MCoT, a small language model (SLM) fine-tuned for content safety moderation leveraging external framework. By training our model on tool-augmented chain-of-thought data generated by LLM, we demonstrate […]

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Retcon — a Prompt-Based Technique for Precise Control of LLMs in Conversations

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arXiv:2603.03317v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) allow agents to execute complex natural language tasks. Many LLM applications, such as support agents, teaching assistants, and interactive bots, involve multi-turn conversations. However, it remains challenging to control LLMs in the context of such interactions, particularly when the LLM behavior needs to be adjustable over the course of the conversation. In this paper, we present Retcon, a few-shot prompting technique designed to provide turn-level control […]

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Coronavirus and Machine Learning Conferences

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I’ve been following the renamed COVID-19 epidemic closely since potential exponentials deserve that kind of attention. The last few days have convinced me it’s a good idea to start making contingency plans for machine learning conferences like ICML. The plausible options happen to be structurally aligned with calls to enable reduced travel to machine learning conferences, but of course the need is much more immediate. I’ll discuss relevant observations about COVID-19 and then the impact on machine learning […]

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How to Build and Deploy a Blog-to-Audio Service Using OpenAI

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Turning written blog posts into audio is a simple way to reach more people. Many users prefer listening during travel or workouts. Others enjoy having both reading and listening options. With OpenAI’s text-to-speech models, you can build a clean service that takes a blog URL or pasted text and produces a natural-sounding audio file. In this article, you will learn how to build this system end-to-end. You will learn how to fetch blog content, send it to OpenAI’s […]

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