Social media’s next evolution: User-controlled algorithms
Social media feeds are becoming more customizable as platforms like Threads, Instagram, and TikTok introduce tools that let users directly influence the algorithms powering their recommendations.
NEA’s Tiffany Luck on AI IPOs, personal agents, and the ROI reckoning
Tokenmaxxing was the hottest trend in Silicon Valley earlier this year, with CEOs encouraging employees to push AI usage as far as it would go. Then the bill came due. Uber reportedly blew through its annual AI budget in a few months, some companies cut Claude licenses for parts of their org, and Me...
Vercel Releases Eve: An Open-Source AI Agent Framework Where Each Agent is a Directory of Files Mapped to Capabilities
Vercel has open-sourced eve, an Apache-2.0 agent framework now in public preview. An agent is a directory of files, with durable execution, sandboxes, approvals, connections, channels, and evals built in. Scaffold with npx eve@latest init and deploy unchanged via vercel deploy.
The post Vercel Relea...
Google bets on Gemini to reinvent the smart home speaker
Google is betting generative AI can breathe new life into the smart speaker. The company's new $99.99 Google Home Speaker replaces the rigid commands of the Google Assistant era with more conversational Gemini interactions.
Is your most capable AI agent also your biggest data leak?
A Microsoft and Huazhong University benchmark tested GPT-4o, GPT-5, Grok-3, and others on realistic enterprise data scenarios. Privacy violation rates hit 50.9%. More capable models made it worse, and the fix has nothing to do with model selection...
The Secret to Reproducible and Portable Optimization: ORPilot’s Intermediate Representation (IR)
Why production-level AI optimization modeling agent needs reproducibility and portability, and how IR helps achieve them
The post The Secret to Reproducible and Portable Optimization: ORPilot’s Intermediate Representation (IR) appeared first on Towards Data Science.
You know the meeting. The board wants an AI agent strategy by end of quarter. Someone on the leadership team has read a McKinsey report. You’ve been voluntold to build the platform. The slide deck says “AI-native.” The acceptance criteria are vague. Somebody mentions LangGraph, and somebody else say...
Most LLM applications need a clear workflow, not an autonomous agent. Here's how to build one in plain Python.
The post You Probably Don’t Need an Agent Framework appeared first on Towards Data Science.
OpenAI Just Launched 3 Free AI Courses with Certificates
Having the right certificate can make all the difference. But with so many out there, getting the right one isn’t easy. That’s where OpenAI Academy comes in. OpenAI, the company behind the ChatGPT models, has introduced a learning platform through its OpenAI academy that offers AI courses for upskil...
MiniMax Sparse Attention (MSA): a Two-Branch Block-Sparse Attention Trained on a 109B-Parameter MoE With a 3T-Token Budget
MiniMax released MSA, a sparse attention built on Grouped Query Attention. A lightweight Index Branch selects Top-k key-value blocks per query and GQA group; the Main Branch attends only to those blocks. It matches GQA on downstream benchmarks while reducing per-token attention compute 28.4× at 1M c...
OpenAI’s Deployment Simulation Extends Pre-Deployment Risk Assessment to Agentic Coding Through Simulated Tool Calls
OpenAI introduced Deployment Simulation on June 16, 2026. The method replays past conversations through a new candidate model before release. It then grades the completions to estimate deployment-time rates of undesired behavior. We break down how the pipeline works, the reported 1.5x median multipl...
Correct When Paired, Wrong When Split: Decoupling and Editing Modality-Specific Neurons in MLLMs
arXiv:2606.17057v1 Announce Type: new
Abstract: Although Knowledge Editing provides an efficient mechanism for updating the knowledge of Multimodal Large Language Models (MLLMs), we find that current paradigms still suffer from an important yet remain underexplored issue : editing decoupling failur...
Informative Missingness to Generate Irregular Clinical Time Series
arXiv:2606.17106v1 Announce Type: new
Abstract: Laboratory tests in electronic health records are collected irregularly, and the absence of a test order can be as informative as the measurement itself. Such missingness reflects clinicians' decisions and patient physiology, making it important to mo...
Models Take Notes at Prefill: KV Cache Can Be Editable and Composable
arXiv:2606.17107v1 Announce Type: new
Abstract: Prefix caching reuses prefill only across an exactly shared prefix, so one changed field invalidates the entire downstream cache. Yet overwriting the field's own key/value vectors and reusing the rest leaves the model acting on the old value. The reas...
The Critical Role of Model Selection in Causal Inference: A Comparative Analysis of Classification Models within the InferBERT Framework for Pharmacovigilance
arXiv:2606.17113v1 Announce Type: new
Abstract: Distinguishing causal adverse drug events (ADEs) from spurious correlations remains a central challenge in pharmacovigilance. The InferBERT framework integrates transformer models with Do-calculus, but its success hinges on the underlying classificati...