Week one of the Musk v. Altman trial: What it was like in the room
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Two of the most powerful people in AI—Sam Altman and Elon Musk—began their face-off in court in Oakland, California, last week. Musk is suing OpenAI, alleging tha...
DoorDash adds AI tools to speed up merchant onboarding, edit photos of dishes
DoorDash on Monday added new AI-powered tools that let merchants speed up onboarding, edit photos to make dishes look better, and create new websites from existing content.
How AI Tools Generate Technical Debt in IoT Systems — and What to Do About It
AI tools speed up IoT development — but closer to the hardware, the same code that looks correct can silently break thousands of devices at once.
The post How AI Tools Generate Technical Debt in IoT Systems — and What to Do About It appeared first on Towards Data Science.
ML Intern in Practice: From Prompt to a Shipped Hugging Face Model
Most ML projects do not fail because of model choice. They fail in the messy middle: finding the right dataset, checking usability, writing training code, fixing errors, reading logs, debugging weak results, evaluating outputs, and packaging the model for others. This is where ML Intern fits. It is ...
Every day, millions of pieces of fake content are produced. Videos, audio clips, posts, articles, generated by artificial intelligence, distributed at industrial scale, aimed at shifting public opinion across entire countries. The people producing them are often outside the country being targeted. T...
Cloud Is Closer Than It Appears: Revisiting the Tradeoffs of Distributed Real-Time Inference
arXiv:2605.00005v1 Announce Type: new
Abstract: The increasing deployment of deep neural networks (DNNs) in cyber-physical systems (CPS) enhances perception fidelity, but imposes substantial computational demands on execution platforms, posing challenges to real-time control deadlines. Traditional ...
What Physics do Data-Driven MoCap-to-Radar Models Learn?
arXiv:2605.00018v1 Announce Type: new
Abstract: Data-driven MoCap-to-radar models generate plausible micro-Doppler spectrograms, but do they actually learn the underlying physics? We introduce a physics-based interpretability framework to answer this question via two proposed complementary metrics:...
AirFM-DDA: Air-Interface Foundation Model in the Delay-Doppler-Angle Domain for AI-Native 6G
arXiv:2605.00020v1 Announce Type: new
Abstract: The success of large foundation models is catalyzing a new paradigm for AI-native 6G network design: wireless foundation models for physical layer design. However, existing models often operate on channel state information (CSI) in the space-time-freq...
TADI: Tool-Augmented Drilling Intelligence via Agentic LLM Orchestration over Heterogeneous Wellsite Data
arXiv:2605.00060v1 Announce Type: new
Abstract: We present TADI (Tool-Augmented Drilling Intelligence), an agentic AI system that transforms drilling operational data into evidence-based analytical intelligence. Applied to the Equinor Volve Field dataset, TADI integrates 1,759 daily drilling report...
AgentReputation: A Decentralized Agentic AI Reputation Framework
arXiv:2605.00073v1 Announce Type: new
Abstract: Decentralized, agentic AI marketplaces are rapidly emerging to support software engineering tasks such as debugging, patch generation, and security auditing, often operating without centralized oversight. However, existing reputation mechanisms fail i...
Minimal, Local, Causal Explanations for Jailbreak Success in Large Language Models
arXiv:2605.00123v1 Announce Type: new
Abstract: Safety trained large language models (LLMs) can often be induced to answer harmful requests through jailbreak prompts. Because we lack a robust understanding of why LLMs are susceptible to jailbreaks, future frontier models operating more autonomously...
Are Tools All We Need? Unveiling the Tool-Use Tax in LLM Agents
arXiv:2605.00136v1 Announce Type: new
Abstract: Tool-augmented reasoning has become a popular direction for LLM-based agents, and it is widely assumed to improve reasoning and reliability. However, we demonstrate that this consensus does not always hold: in the presence of semantic distractors, too...
TUR-DPO: Topology- and Uncertainty-Aware Direct Preference Optimization
arXiv:2605.00224v1 Announce Type: new
Abstract: Aligning large language models (LLMs) with human preferences is commonly done via reinforcement learning from human feedback (RLHF) with Proximal Policy Optimization (PPO) or, more simply, via Direct Preference Optimization (DPO). While DPO is stable ...
AI Weekly Issue #489: PE built AI's new distribution layer
Quick Hits
WSJ: OpenAI execs overruled employees who urged the company to alert police about Tumbler Ridge shooter's ChatGPT threats — The shooter had used ChatGPT to draft and rehearse threats; staff escalated internally; leadership kept it in-house. The threats were real. WSJ has the timeline. Ev...
PORTool: Importance-Aware Policy Optimization with Rewarded Tree for Multi-Tool-Integrated Reasoning
Multi-tool-integrated reasoning enables LLM-empowered tool-use agents to solve complex tasks by interleaving natural-language reasoning with calls to external tools. However, training such agents using outcome-only rewards suffers from credit-assignment ambiguity, obscuring which intermediate steps ...
A Coding Implementation to Explore and Analyze the TaskTrove Dataset with Streaming Parsing Visualization and Verifier Detection
In this tutorial, we take a deep dive into the TaskTrove dataset on Hugging Face and build a complete, practical workflow to efficiently explore it. Instead of downloading the full multi-gigabyte dataset, we stream it directly and work with individual samples in real time. We begin by setting up the...
Sakana AI Introduces KAME: A Tandem Speech-to-Speech Architecture That Injects LLM Knowledge in Real Time
Sakana AI Introduces KAME: A Tandem Architecture That Injects Real-Time LLM Knowledge Into Speech-to-Speech Conversational AI Without Adding Latency
The post Sakana AI Introduces KAME: A Tandem Speech-to-Speech Architecture That Injects LLM Knowledge in Real Time appeared first on MarkTechPost.
Projects are the bridge between understanding AI and actually building with it. While the last couple of years were dominated by generative models, the shift now is toward systems that can think in steps, use tools, and act with a clear objective. This guide brings together over 15 solved agentic AI...