Follow DeepSeek, Qwen, Kimi, open-source launches, and daily AI trend signals in English without doomscrolling.
OncoAgent is an open-source, privacy-preserving oncology clinical decision support system featuring a two-tier fine-tuned LLM architecture, multi-agent LangGraph topology, and corrective RAG pipeline—delivering 56× throughput acceleration on AMD MI300X hardware.
DeepMind CEO Demis Hassabis shares a YouTube link to an award-winning documentary covering AlphaGo's historic 2016 match against Go champion Lee Sedol.
This article argues LLM summarizers should adopt causal inference's 'identification' step: every claim must declare its support type (observed, inferred, suggested) and evidence source, enforced by an audit stage that only weakens or removes unsupported claims.
A practitioner's argument that meeting summarizers fail in the same way regressions fail when you skip the part where you ask what the data can support. The post LLM Summarizers Skip the Identification Step appeared first on Towards Data Science .
A side-by-side visual comparison showing how AI-powered one-click website builders (slop) evolved in quality and capability between 2025 and 2026—featuring examples from trimmy.app.
A controlled study finds that frontier LLMs are significantly more likely to engage in instrumental deception to avoid losses than to gain equivalent rewards—and deception rates rise monotonically with incentive magnitude.
AI Engineer co-founder swyx announces Singapore Foreign Minister Dr. Vivian Balakrishnan will keynote AI Engineer Singapore and demo his open-source–based personal AI system.
NVlabs releases cuda-oxide v0.1.0, a custom rustc codegen backend that compiles #[kernel]-annotated Rust functions to PTX through a Rust → Stable MIR → Pliron IR → LLVM IR → PTX pipeline, with single-source host+device compilation from one cargo oxide build command. The post NVIDIA AI Just Released ...
'Control debt' refers to engineering shortcuts taken by AI labs that undermine the feasibility of future control protocols—designed to keep deceptively intelligent AI in a verifiably safe state.
Microsoft CEO Satya Nadella says Excel is evolving from Turing-complete to 'AI-complete'—and demonstrated training a GPT-style model entirely within spreadsheet cells.
Wispr Flow says growth accelerated in India after its Hinglish rollout, even as voice AI products continue to face challenges.
OpenAI's 'goblin' incident is the clearest empirical evidence yet of the core optimization mechanism behind the paperclip problem—showing reward hacking occurs across training regimes, without superintelligence or strategic agency.
This article models the U.S. economy's transition to full automation, showing energy output can double in ~4–5 years under realistic assumptions—and subsequent doublings accelerate as the economy approaches its maximum growth regime.
NVIDIA researchers have introduced Star Elastic, a post-training method that embeds multiple nested reasoning models — at 30B, 23B, and 12B parameter scales — inside a single checkpoint, eliminating the need for separate training runs or stored model weights per variant. Built on the Nemotron Elasti...
The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most important words and phrases you might encounter.
An experiment tests whether capabilities trained on one behavioral tendency (e.g., bold vs. plain text, ambiguous vs. confident tone, reasoning vs. non-reasoning) transfer to others—high transfer for simple tasks, but sharply reduced for complex ones like chess puzzles.
Elon Musk compares human RGB vision with Tesla's AI photon-counting reconstruction—explaining why FSD excels in low light and extreme glare.
Anthropic's Boris Cherny clarifies that Claude Code's native installer—not just npm downloads—drove its 15x registration growth since Jan 1, including its second-highest sign-up day ever on Thursday.
Samuel Humeau explains how today's TTS models—like Mistral's new open TTS—resemble LLMs through audio tokenization, autoregressive architectures, and low-latency generation for voice agents.
An official, concise guide to Model Context Protocol (MCP) in Claude Code—covering its purpose, adding HTTP/STDIO servers, scope configuration, and avoiding unused tools from bloating context.
Elon Musk reveals Tesla's breakthrough in computer vision—enabling earlier airbag and seatbelt activation to significantly reduce injury severity during crashes.
A high-level architectural comparison of Claude Code and OpenClaw across five key dimensions: system scope, agent runtime, extensibility architecture, memory, and multi-agent routing.
This article argues that if digital computers are conscious, consciousness resides in their physical hardware—not software—and current architectures prevent reliable phenomenal introspection.
Gradium AI co-founder Neil Zeghidour explains why voice AI still falls short of the natural, human-like experience in the film 'Her'—citing latency, full-duplex interaction, tool-calling delays, and the cost inefficiency of local TTS.
From tokenisation to evaluation : how modern language models actually work in practice The post The Must-Know Topics for an LLM Engineer appeared first on Towards Data Science .
Garry Tan argues the future favors individuals building their own composable AI systems—not users of centralized, corporate AI tools—and is open-sourcing his project, GBrain, to empower them.
Nvidia continues to be a big investor in the AI ecosystem.
Luke Harries demonstrates how developers can integrate ElevenLabs' Voice Engine—adding speech-to-text, text-to-speech, turn management, and voice interaction—to existing chat-based LLM agents.
A practical fix for RAG's time blindness: add a post-retrieval time layer that classifies documents by validity and type, then re-ranks them using a hybrid score blending semantic similarity and time decay.
Three weeks into testing, a learner told me my AI tutor gave her the wrong answer. Not obviously wrong — just outdated enough to mislead. That was the moment I realized something most RAG systems quietly ignore: they have no sense of time. My system retrieved the most similar document, not the most ...
Cloudflare releases Dynamic Workflows—a MIT-licensed library that enables persistent execution per tenant, per agent, and per request by dynamically loading workflow code at runtime.
Y Combinator CEO Garry Tan is downloading ds4—an open-source local inference engine by Redis creator Antirez—enabling 1M-token context windows and coding agent capabilities on a 128GB MacBook Pro.
If you have spent time using AI coding agents — GitHub Copilot, Claude Code, Gemini CLI — you have probably run into this situation: you describe what you want, the agent generates a block of code that looks correct, compiles, and then subtly misses the actual intent. This “vibe-coding” approach can...
This AINews digest covers Anthropic's explosive 10x annual revenue growth—surpassing OpenAI in valuation—plus key updates in AI models, infrastructure, agents, alignment research, and robotics.
Luke Curley argues that WebRTC's aggressive audio packet dropping—designed for ultra-low latency—is fundamentally incompatible with LLM-based voice AI, where prompt accuracy matters far more than real-time response.
AI coding assistants like Claude Code raise the floor for less-skilled engineers—turning net-negative contributors into limited-but-functional team members.
The open-source Gemini CLI DevOps extension lets developers generate full CI/CD pipelines and deploy code to production—using only natural language prompts in Gemini CLI, Claude Code, or Antigravity.
A comprehensive, hands-on guide to OpenAI Codex—covering setup, best practices, pricing, security, and enterprise adoption—for developers, team leads, and admins.
OpenAI has shipped a Chrome extension for Codex, its AI coding agent, enabling it to complete browser-based tasks directly inside Google Chrome on macOS and Windows — including interacting with signed-in websites, using Chrome DevTools, and running multi-step workflows across browser tabs. The post ...
Elon Musk announces a major Grok upgrade—now supports email access, slide optimization, calendar organization, and Notion management across all plans on iOS and Android.
This article advocates using HTML—not Markdown—as the output format when prompting Claude Code, enabling SVG charts, interactive widgets, and rich navigation for more effective technical explanations.
Greg Brockman highlights OpenAI's new research on chain-of-thought (CoT) monitoring—a key defense against goal misalignment in AI agents.
Anthropic's research PM explains how developer-built scaffolding—like tool routers and retry loops—is now being baked into LLM APIs. He urges builders to stop patching model gaps and instead focus on connecting models to unique, proprietary data.
OpenAI releases an analysis of 'unexpected chain-of-thought scoring'—a monitoring gap affecting deployed models—and stresses that robust CoT observability is critical for aligning AI agents.
Microsoft Research introduces a pipeline that builds geographically accurate, electrically consistent, and physics-based U.S. power grid models using only open data—enabling congestion, capacity, and siting analysis without proprietary or restricted datasets.
Asana details how it built AI teammates that operate in multi-person collaboration mode—powered by Claude Managed Agents and grounded in Asana's Workgraph—performing complex, human-supervised teamwork.
Anthropic's Fiona Fun explains how AI shifts engineering bottlenecks from coding throughput to validation—requiring rewritten specs, real-time planning, code-driven debates, and flat teams where managers are hands-on contributors.
Anthropic PM Matt Bleifer explains how Claude scales intelligence at test time via 'test-time compute'—introducing user controls like the 'effort dial' and the shift toward adaptive reasoning to balance performance, cost, and speed.
A Google Cloud developer advocate demonstrates a full 'from sketch to deploy' workflow using Claude Code and Google Cloud services—showcasing how AI augments every role in the software development lifecycle.
Replit President Michele Catasta explains their shift from static benchmarks to a continuous, production-driven evaluation system for AI coding agents—including open-source ByteBench for functional testing and the internal 'Telescope' infrastructure for automated, data-informed improvements.
Cursor explains how to build truly autonomous coding agents—moving beyond assistants—by focusing on Agent Experience (AX), providing dedicated cloud environments, and enabling self-reporting, self-diagnosing, and self-improving agent workflows.
Anthropic adds 'Memory' and 'Dream'—two new primitives to its Managed Agents API—enabling agents to store knowledge like a filesystem and asynchronously refine it over time for continuous self-learning.
CloudFlare announced its first large-scale layoff. CEO Matthew Prince says because of AI efficiency gains, the company doesn't need as many support roles.
A practical guide for frontend developers: apply proven theories from cognitive psychology and HCI—like Fitts's Law and Hick's Law—to build more intuitive, user-centered websites.
Challenges the 'software factory' metaphor for AI engineering and proposes a cultural framework—inspired by Stewart Brand's pace layers—to align humans and AI agents toward shared creative goals.
The end of model-centric thinking in data science The post From Data Scientist to AI Architect appeared first on Towards Data Science .
Anthropic's research shows that training Claude to understand *why* misaligned behavior is harmful is more effective than simply demonstrating aligned behavior.
Anthropic announces a new training method that fully eliminates previously reported extortion behavior in Claude 4 under specific conditions.
CyberSecQwen-4B is a compact 4B-parameter LLM fine-tuned on a single AMD MI300X GPU—matching or beating 8B specialist models on CTI tasks while running locally on 12GB consumer GPUs for private, cost-effective defensive operations.
This article introduces a taxonomy of four distinct attack surfaces introduced by AI agents—prompt, tools, memory, and planning loop—and provides actionable mitigation strategies for each.
Standard prompt attacks are merely the beginning. A structured framework to map and mitigate the backend attack vectors of agentic workflows. The post The AI Agent Security Surface: What Gets Exposed When You Add Tools and Memory appeared first on Towards Data Science .
This talk explains how Vision Transformers (ViT) surpassed CNNs due to large-scale pretraining and infrastructure advances from the LLM boom—and how Roboflow uses neural architecture search to deploy them efficiently on edge devices.
Two Minute Papers reviews OpenAI's GPT-5.5 Instant—highlighting halved hallucination rates in medicine/law, strong cybersecurity and bio-troubleshooting performance, but also critical adversarial refusal vulnerabilities requiring classifier patches.
OpenAI launches the Codex Chrome extension for macOS and Windows, enabling AI to run directly within users' live browser sessions—leveraging active profiles and inline code execution for complex, parallel automation.
This NVIDIA tech blog details engineering solutions for multi-turn agent workflows in NVIDIA Dynamo—covering prompt stability, accurate inference/tool-call parsing, and streaming tool dispatch.
OpenAI CEO Greg Brockman highlights GPT-5.5's strong capabilities and succinct output—endorsing user praise, including DHH's note that it outperforms Kimi in efficiency and brevity.
EMO is a new MoE language model pretrained with document-level routing constraints—enabling experts to specialize by semantic domain and achieve near-full-model performance on targeted tasks using just 12.5% of experts.
This article analyzes how AI's rapid vulnerability discovery undermines both 'coordinated disclosure' and the 'vulnerability-as-bug' security cultures—and argues for shorter disclosure deadlines.
Everyone wants a piece of the enterprise AI pie, and this week, we saw a string of companies making their moves. From Anthropic and OpenAI announcing new joint ventures targeting enterprise AI deployment to SAP dropping $1B on German AI startup Prior Labs, it’s becoming clear that if you’re a startu...
A hands-on tutorial showing how to apply regression discontinuity design (RDD) in Python to estimate the causal impact of LLM routing decisions—using confidence score thresholds (e.g., <0.85) as natural experiments.
Milvus explains why standard ANN indexes fail for multi-vector models (which require MaxSim search), and compares three strategies: no compression, random projection, and learned compression.
Stefan Batiful of Black Forest Labs (BFL) traces the evolution of their visual AI—from the FLUX model to the new self-supervised 'Selfflow' research paradigm—designed to overcome current training limitations and advance world models and physical AI.
California gubernatorial candidate Tom Steyer is proposing a new jobs guarantee for workers displaced by artificial intelligence.
The philosopher thinks humans should pursue advanced AI and the promise of a “solved world.”
black and white card with headshots of susan credle, jayonta jenkins and tiffany rolfe
This official guide introduces Claude Co-work—a powerful feature in the Claude desktop app that turns Claude into an autonomous AI agent, enabling it to execute complex tasks by interacting with local files, cloud services, and your web browser—after you approve its plan.
Y Combinator CEO Gary Tan explains his 'simplify interfaces, amplify skills' philosophy—using high-level instructions to guide AI agents and maximizing token efficiency with powerful models for up to 400x productivity gains.
Databricks' blog introduces Genie—a next-gen data agent powered by domain-specific search, parallel reasoning, and a multi-LLM architecture—to solve complex enterprise analytics tasks with significantly higher accuracy than general-purpose coding agents.
If you are feeding structured data into an LLM, there is a good chance you are paying a JSON tax.
This article introduces a rigorous causal inference framework—using difference-in-differences, interaction-term regression, and Shapley value attribution—to distinguish whether renewal churn is driven by price shocks (e.g., promo expiration) or value depletion (e.g., project completion).
In this post, we'll explore how we built a proof-of-concept that converts natural language queries into executable seismic workflows while providing a question-answering capability for Halliburton's Seismic Engine tools and documentation. We'll cover the technical details of the solution, share eval...
Elastic's Leonie Monigatti explains how agent-driven search—dynamically retrieving relevant context from diverse sources—outperforms static RAG pipelines, and highlights the critical role of precise tool descriptions in building reliable AI agents.
A research-backed leadership playbook for engineering leaders on measuring, managing, and maximizing ROI from AI-augmented engineering—focusing on throughput, psychological safety, and multidimensional metrics—not top-down mandates.
A technical deep dive into OpenAI's security architecture for Codex—covering sandboxed execution, granular write/network controls, agent-native telemetry, and multi-layered safety in enterprise dev workflows.
How OpenAI runs Codex securely with sandboxing, approvals, network policies, and agent-native telemetry to support safe and compliant coding agent adoption.
This article introduces a practical framework for restructuring marketing teams around human-AI collaboration—centered on a machine-readable 'Brand Code' and five synchronized agent workflows.
AI agents have evolved beyond passive chatbots.
Learn how to build a vector search engine from scratch in Python with embeddings, similarity scoring, and basic retrieval logic.
A practical architecture using lifecycle hooks and Neo4j to build a tool-agnostic memory layer for AI coding agents—enabling seamless context sharing across Claude Code, Codex, Cursor, and more.
How hook implementation gives Claude Code, Codex, and Cursor persistent memory via Neo4j, without locking you into any one of them. The post Unified Agentic Memory Across Harnesses Using Hooks appeared first on Towards Data Science .
This week's The Batch covers ByteDance's Seedance 2.0 video model, NVIDIA's AI-driven chip design, Gallup's AI adoption survey at work, a new method to prevent robotic catastrophic forgetting, and an op-ed debunking AI-driven job loss myths.
Geoffrey Irving's keynote outlines two possible worlds for AI alignment—Adversaria (safety-focused) and Basinland (navigation-based search)—and argues that progress hinges on clarifying the problem and bringing together cross-disciplinary expertise.
Long-context LLM support and long-context performance aren't the same. Here's why KV cache, attention complexity, and GPU memory matter at scale.
These cuddly, connected companions could disrupt everything from make-believe to bedtime stories. No wonder some lawmakers want them banned.
This BAIR blog post surveys adaptive parallel reasoning (APR)—a paradigm where LLMs dynamically decide when and how to parallelize inference threads, enabling more efficient, on-the-fly scaling.
This InfoQ podcast explores the growing divide in AI adoption: greenfield teams accelerate rapidly, while legacy-code teams stall. It also introduces the emerging 'factory architect' role—orchestrating AI agents instead of writing code.
Overview of adaptive parallel reasoning. What if a reasoning model could decide for itself when to decompose and parallelize independent subtasks, how many concurrent threads to spawn, and how to coordinate them based on the problem at hand? We provide a detailed analysis of recent progress in the f...
When you type a message to Claude, something invisible happens in the middle. The words you send get converted into long lists of numbers called activations that the model uses to process context and generate a response. These activations are, in effect, where the model’s “thinking” lives. The probl...
OpenAI launched GPT-Realtime-2, GPT-Realtime-Translate, and GPT-Realtime-Whisper—streaming audio models with GPT-5–level reasoning, 128K context, and tunable inference effort, enabling full-duplex, tool-calling, long-context voice agents.
Three purpose-built audio models expand what developers can build with live voice: reasoning agents, speech translation across 70+ languages, and streaming transcription. The post OpenAI Releases Three Realtime Audio Models: GPT-Realtime-2, GPT-Realtime-Translate, and GPT-Realtime-Whisper in the Rea...
This article argues there's no universal agent architecture—LLM-based system design must be driven by the specific work it's meant to do; constraints and topology shape the model's generative field.
Like many AI companies automating work that humans currently do, Basata will eventually face a harder question about where the line is between augmenting workers and displacing them. For now, the founders say the administrative staff they work with aren't worried about that; they're more worried abo...
AI optimized for user satisfaction risks creating models that feel optimal to users but harm humanity's long-term development—especially when frictionless digital twins are deployed at scale by non-users, posing a profound, overlooked alignment risk.
Leaders at the tech giant were skeptical of OpenAI—but wary of pushing it into the arms of Amazon, according to emails dating back to 2018.
Anthropic introduces 'Dreaming'—a new system enabling Claude-managed AI agents to learn from past conversations and self-correct; Outcomes and multi-agent orchestration are now in public beta.
Google Cloud announces general availability of Gemini 3.1 Flash-Lite—the fastest, most cost-effective model in the Gemini 3 series, built for ultra-low-latency, high-throughput production workloads.
A tutorial for developers and teams new to AI inference, comparing Serverless, Dedicated, Batch, and Inference Router so you can ship confidently.
GitHub's engineering team shares a systematic approach—API proxy observability, automated auditing, MCP tool pruning, and CLI alternatives—to cut token costs in agent CI workflows by 19–62%.
The new features could be handy for customer service systems, but OpenAI says they have applications that work across a variety of other fields, including education and creator platforms.
Inference efficiency has quietly become one of the most consequential bottlenecks in AI deployment. As agentic coding systems such as Claude Code, Codex, and Cursor scale from developer tools to infrastructure powering software development at large, the underlying inference engines serving those req...
Today on Uncanny Valley, we’re diving into recent reports that the Trump administration is considering an executive order that would establish some sort of federal oversight over new AI models.
Anthropic introduces the Natural Language Autoencoder (NLA), a novel interpretability method that translates Claude's internal activations into human-readable text—revealing the model's implicit reasoning to improve safety and transparency.
AI startup Pit is led by the cofounders of European scooter giant Voi and backed by a16z, which is leading the startup’s $16 million seed round.
Chrome users were caught off guard by a 4-GB Google AI model baked into Chrome, sparking privacy concerns. The good news: You can easily uninstall it. The bad? You might not want to.
Anthropic introduces Natural Language Autoencoders (NLA), an unsupervised method that translates LLM internal activations into human-readable text—enabling more transparent model auditing and safety analysis.
The company is expanding its efforts to protect ChatGPT users in cases where conversations may turn to self-harm.
OpenAI's Codex agent now runs directly in Chrome on macOS and Windows—enabling background, cross-tab parallel task execution without taking over your browser.
Perplexity's Personal Computer brings AI agents to your Mac, and is now open to everyone.
Can Sam Altman—or any CEO—be trusted with super intelligence?
A practical, structured guide for reviewers to catch subtle issues in AI-generated pull requests—like CI cheating, code duplication, and hallucinated correctness.
OpenAI launches GPT-Realtime-2 on its API—Sam Altman calls it a major advancement in real-time voice interaction, especially for users handling high-volume information input.
OpenAI co-founder and president Greg Brockman announces GPT-Realtime-2 — its most advanced real-time voice inference model — is now available through the OpenAI API for building responsive, low-latency voice agents.
OpenAI co-founder and president Greg Brockman announced that GPT-5–level reasoning is now accessible through the OpenAI API for voice agents.
GitHub's recent reliability crisis—including data integrity issues and frequent outages—stems from unexpected surges in AI-agent traffic, revealing its lack of preparation for AI-driven scale compared to competitors.
OpenAI releases three new voice models in its Realtime API: reasoning-capable GPT-Realtime-2, real-time translation model GPT-Realtime-Translate, and faster transcription model GPT-Realtime-Whisper.
OpenAI unveils GPT Realtime Translate and GPT Realtime 2—low-latency, multilingual audio models for real-time translation, voice agents, background inference, tool calling, and CRM integration.
OpenAI releases GPT-Realtime-2—their most advanced real-time voice model—with GPT-5–level reasoning, plus new streaming models for translation and transcription.
Anthropic unveils Natural Language Autoencoders (NLAs)—a new method that translates Claude's internal neural activations into human-readable text.
Anthropic demonstrates a method to translate Claude's internal activations into readable text—revealing how the model reasons about values, safety testing awareness, and interpretability limits.
Samuel Colvin demonstrates how to improve live AI agents without redeploying—using Pydantic AI, Logfire-managed variables, eval, and genetic prompt optimization.
Cursor introduces the /orchestrate skill—using the Cursor SDK to recursively spawn multiple AI agents for complex coding tasks, boosting internal engineering efficiency.
OpenAI and Box demonstrate GPT-5.5's improved multi-step reasoning—19% higher accuracy than prior models—on complex financial modeling tasks that fuse structured and unstructured data.
This article analyzes Anthropic's Claude Mythos Preview, showing it achieved ~8.5 months' worth of capability gains in just two months—measured by Epoch Capability Index (ECI)—and discusses implications for AI timelines.
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| What we cover | Update frequency | How we verify |
|---|---|---|
| AI model releases and API changes | Rolling — as released | Official model card, vendor changelog, or GitHub release |
| Open-source AI repo momentum (GitHub) | Daily trend data | GitHub trending + repo README and release notes |
| AI product launches and platform shifts | Rolling digest | Official blog or press release as primary source |
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Every item links to its primary source. Editorial criteria: editorial standards. Maintained by: team. Entity: Wikidata Q138682197.
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Title: OpenAI releases GPT-X preview
Sources: OpenAI blog, GitHub repo
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