Here's my current tech stack for scaling consumer apps in 2026. It's by far the best & cheapest stack for agent-native development ⬇️ https://t.co/0yqdwDeCp5
#English text is being prepared.#Agents#English text is being prepared.
GPT-6.1 Terra beats Astra in our vision benchmarks wtf OpenAI? had to double-check the results - text - object detection - counting also ~47% faster and ~92% cheaper ↓ leaderboards and examples https://t.co/4AvboaD16g
#Evaluations / benchmarks#Multimodal#OpenAI
#Tutorials / practice#Agents#English text is being prepared.
#Evaluations / benchmarks#English text is being prepared.#Agents
#English text is being prepared.#Multimodal#Video
GPT-6.1 Terra: delivering fast and capable computer use at a lower price. GPT-6.1 Terra understands what’s on screen, takes action across apps, writes naturally, and is a more capable model for your whole workday with the efficiency to take on more of it. https://t.co/8JTN1yonmV
#Evaluations / benchmarks#English text is being prepared.#OpenAI
On October 27, 2026, Perplexity published an LLM gateway best practices guide explaining how this middleware layer routes, authenticates, caches, and logs model calls, and distinguishing four categories: API gateways, LLM gateways, MCP gateways, and AI gateways. The guide breaks down the mechanism through a six-step request lifecycle, while warning that the gateway centralizes credentials from various providers, and cites the LiteLLM gateway breach disclosed by Microsoft and two high-severity vulnerabilities, CVE-2026-35029 and CVE-2026-59823, reported by Check Point (already fixed in LiteLLM 1.83.9). The article also lists postmortems of Cloudflare AI Gateway and OpenRouter outages, four deployment paths, and paid plans starting at about $50 per month.
#Safety / alignment#English text is being prepared.#OpenAI
Leikeji experienced the Rokid Glasses 2, released on October 27, in advance. It starts at 3,699 yuan (3,199 yuan after national subsidy), and officially goes on sale on November 11. Compared with the previous generation, the new model's temples use a more skin-friendly material to distribute pressure, the battery capacity has increased to 263mAh, up 25%, and it is equipped with a 12-megapixel camera supporting 4K 30fps and 2K 60fps video recording. In the author's test, after 20 minutes of navigation, 30 minutes of music, and 30 minutes of photo and video recording, more than half of the battery remained, and magnetic charging can reach 75% in 20 minutes.
#Product updates#English text is being prepared.#Evaluations / benchmarks
NVIDIA has released the Nemotron-Personas France and Belgium datasets and provided a complete post-training workflow for fine-tuning Nemotron 3.5 Lightning with them. The workflow includes defining behavior contracts, generating synthetic conversations with personas, fine-tuning with LoRA on NVIDIA NeMo, merging adapters, and then comparing and evaluating item by item against the base model on a frozen test set. The France dataset was built in collaboration with Pleias, and the Belgium dataset involved Pleias and KU Leuven; the Nemotron repository provides reusable steps and agent skills for data generation, training, and evaluation.
#Tutorials / practice#English text is being prepared.#Open-source ecosystem
LangChain's GTM engineering team, working with the design team, built Content Studio, a design agent inside Slack, on Managed Deep Agents. It can generate videos, social graphics, UI mockups, and slide decks, and has already produced more than 3,000 assets and over 80 slide decks. The article breaks down its four-layer knowledge structure (skills, wiki, code validation, memory), the dedicated LangSmith Sandbox for each Slack thread, the two rendering engines HyperFrames and the in-house motion-studio, and how the main agent orchestrates asynchronous sub-agents. The team says that after migrating to Managed Deep Agents, its own code shrank by about 80%, the median model cost per request fell from about $8 in mid-September to about 50 cents, and the entire harness has been open-sourced.
#Tutorials / practice#Agents#English text is being prepared.
Google's Gemini 4 Carbon ranks first on the Artificial Analysis Intelligence Index v5 with a score of 59, leading in four of the 9 evaluations: HLE-Diamond, Terminal-Bench-Science, AA-Omniscience, and AutomationBench-AA. On the Coding Agent Index, Gemini 4 Carbon (high) paired with the Antigravity CLI scores 59, trailing Claude Code paired with Claude Opus 5.5 (max, 62 points) by 3 points. The model has a 1M-token context window, supports text, image, video, and speech input, and is priced at a standard rate of $4/$20 per million input/output tokens; it is currently available to select users with a 50% discount.
#Evaluations / benchmarks#Google#Reasoning
#Tutorials / practice#Agents#English text is being prepared.
The Alibaba Cloud Developer Community has released a GEO practical guide, offering a complete implementation path from AI health self-check to content overhaul, trustworthy signal building, and monthly monitoring. The article recommends selecting 3–5 mainstream AI tools (such as ChatGPT, ERNIE Bot, Doubao, Kimi, and Tencent Yuanbao) and using standardized questions to test brand mentions and recommendation status as an optimization baseline. The content overhaul section proposes four types of approaches—structuring, factualization, Q&A formatting, and de-marketing—and lists five common misconceptions, including treating GEO as SEO and optimizing only the official website.
#Tutorials / practice#Search#English text is being prepared.
The author tested on Alibaba Cloud Bailian 2.5.0. After declaring web_search via the tools parameter, the model went from refusing to answer "today's weather in Shanghai" in 9.2 seconds to returning the day's actual conditions in 24.5 seconds with the correct date. Adding web_extractor lets the model decide the number of retrieval rounds and scraping targets on its own; in the JSON output, the counts of two web_search calls and three web_extractor calls match the per-call records. The author also recorded web-enabled call latency ranging from 17 to 127 seconds and 22,789 input tokens in a single call, and notes that the agent and agent_max strategies other than turbo incur an additional charge per call.
#Tutorials / practice#Agents#English text is being prepared.
#Tutorials / practice#Agents#Evaluations / benchmarks
I've been dogfooding "skill-diet", a skill for slimming down agent skills and keeping them correct. most skills load far more text than a task needs, and some parts often go stale. it also gets worse over time as AI updates skills. skill-diet cuts what the model already does without being told, moves rarely needed detail into files it only reads when needed, and fixes what no longer matches the tool. then it runs the same tasks with the old skill, the new one and no skill, and keeps the new one only if agents do at least as well. on my own skills: 70–80% fewer tokens, same results. https://t.co/h1BnVt7NjD
#English text is being prepared.#Agents#Evaluations / benchmarks
WIRED reporter Reece Rogers spent a day testing six always-on AI agents on an iPhone—Meta Muse, OpenAI Dots, Instinct, Anthropic Claude Duet, Google Gemini Spark, and xAI Grok Bot—scoring them from 1 to 5 across five tests: a morning news briefing, ordering lunch, a calendar conflict reminder, a travel itinerary, and a late-night task. OpenAI Dots performed best overall. Dots costs $100 per month, making it the most expensive in this test, and the author suggests most people wait for a price cut or a free version before trying it. The free and easy-to-use Meta Muse came right behind in total score, Anthropic Claude Duet was rated as having the best interface, and Instinct was rated as the most annoying.
#Evaluations / benchmarks#Agents#OpenAI
MIT Tech Review explains how solid-state transformers use power semiconductors combined with magnetic components to replace the traditional copper-wire-and-iron-core approach, shrinking volume to about one-tenth while keeping capacity unchanged. A 1-megawatt prototype from Srdjan Lukic's team at North Carolina State University achieved about 98% efficiency in EPRI testing, roughly half the losses of the traditional transformer-plus-rectifier combination at about 96%. Such devices are still in the development stage; in the near term they are mainly aimed at powering data center racks, and adapting them to transmission-level high voltages will require further engineering development.
#Industry news#English text is being prepared.#Tutorials / practice
This new-ish 35B multimodal model went from 3.38 → 20.51 tps on an iPhone. MiniCPM-V 4.7 35B-A3B was updated to decode faster on the iPhone by improving how it moves the model between storage and memory. Constraints 🧠 35B total / ~3B active 📱 iPhone 18 Pro Max — 12GB RAM 👁️ image + multi-image + video understanding Most of those 35B weights don't sit in RAM. The experts can stay in the phone's flash storage and get loaded when they're actually needed. Normally that's slow 🐌 SSD expert loading → 3.38 t/s So OpenBMB built Lookahead Expert Scheduling (LES) It predicts which experts the next layer will probably need and starts loading them while the current layer is still computing. Then they stacked the optimizations: 💾 baseline SSD loading → 3.38 tps 👀 expert lookahead → 6.57 ⚙️ optimized scheduling/loading → 11.34 🗜️ mixed-precision quantization → 17.16 🚀 + DSpark speculative decoding → 20.51 tps That's a 6.07× speedup over the same-phone unoptimized baseline. ⚠️ And these are still OpenBMB's own measurements. Link in ALT
#Industry news#English text is being prepared.#Reasoning
The author describes building a QQ chat companion bot on their own server using the open-source project Warm Isle, with DeepSeek generating replies and NapCat handling QQ login, while persona, long-term memory, and proactive messaging are implemented by Warm Isle. The article provides complete steps for Docker deployment, QR code login, persona configuration, and memory extraction, and lists practical pitfalls such as memory usage, SQLite backups, and group chats not being processed by default. The project uses the AGPL-3.0 license, and commercial use is prohibited for the NapCat and SnowLuma protocol ends.
#Tutorials / practice#Agents#Open-source ecosystem