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New features, redesigns and pricing in AI products — whose product got better, pricier or finally usable.

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Feb 13Friday

OpenAI News

Beyond rate limits: scaling access to Codex and Sora

OpenAI says in the headline it will scale access to Codex and Sora beyond current rate limits. The body is empty and does not disclose quota changes, eligible users, pricing, or rollout timing. The key missing fact is the access mechanism, not the headline claim.

Why it matters: This is an official OpenAI product update, so HKR-H and HKR-R pass: the rate-limit angle is clickable and quota pain resonates with users. HKR-K fails because the body discloses no quota delta, eligible tiers, pricing, or rollout date, so it stays at the featured floor.

Feb 12Thursday

OpenAI News

Introducing GPT-5.3-Codex-Spark

OpenAI posted an item titled “Introducing GPT-5.3-Codex-Spark,” confirming the model name GPT-5.3-Codex-Spark. The body is empty in the RSS snippet, so pricing, context window, launch scope, and code-specific details are not disclosed.

Why it matters: An official OpenAI post confirms a new model name, so HKR-H and HKR-R pass on novelty and developer attention. HKR-K fails because the body discloses no specs, pricing, context window, benchmarks, or product scope, keeping this at the featured floor.

Feb 9Monday

36Kr (direct RSS)

Voice Ask is live: why is Xiaohongshu pushing search-by-question?

Xiaohongshu fully launched Voice Ask on Jan. 27, letting users long-press to speak on the search page and get structured answers distilled from in-app user experience posts. The post says it can handle 3-minute spoken queries, foreign languages, and dialects, but does not disclose the model, ASR stack, latency, or accuracy. The real shift is from 3-4 character keyword search to longer spoken questions, widening search intent capture and scenario coverage.

OpenAI News

Testing ads in ChatGPT

OpenAI is testing ads in ChatGPT; the only confirmed fact is that this is a test, not a full rollout. The post body is empty, so placement, audience scope, timeline, and pricing mechanics are not disclosed. Watch whether default traffic surfaces become monetized.

Why it matters: Official source authority puts this in featured range: HKR-H lands because “ads in ChatGPT” is a sharp hook, and HKR-R lands because it hits commercialization of the default AI entry point. HKR-K misses because the body discloses no placement, scope, timeline, or pricing.

36Kr (direct RSS)

Qwen’s 10 Million Milk Teas: How Alibaba’s Massive AI Freebie Campaign Unfolded

Alibaba’s Qwen drove over 10 million orders via a Feb. 6 free-order campaign, but the app slowed and crashed from 10 a.m. to noon as load exceeded capacity; orders had already passed 2 million before noon. 36Kr says initial server capacity was only about one-third of the expected peak, and the subsidy pool was framed as 3 billion yuan; the real signal is not a model leap but a paid test of AI commerce entry and consumer acquisition.

Why it matters: HKR-H lands on the free-milk-tea plus outage hook, while HKR-K lands on concrete scale and capacity numbers. HKR-R also lands because the story speaks to AI distribution, subsidy economics, and infra reliability, but it remains a single-company promo test rather than a market-shi

Jan 30Friday

Bloomberg Technology

Apple Buys Israeli AI Startup Q.ai That Interprets Facial Movements

Apple has acquired Israeli AI startup Q.ai, which builds tech to read facial movements and interpret silent communication. The RSS snippet confirms the deal and focus, but the post does not disclose price, team size, or Apple integration plans. The key question is whether Apple folds this vision capability into accessibility, AirPods, or Vision products.

Why it matters: Bloomberg gives this enough source authority for the featured floor: Apple buying silent-communication vision tech lands HKR-H and HKR-R. HKR-K is weaker because the report discloses no price, team size, accuracy, or integration plan.

Jan 29Thursday

Ruan YiFeng's Weblog

Kimi’s integrated stack vs. Manus’s layered approach

Kimi released the K2.5 model and K2.5 Agent together, with an agent mode already available on its website. The post cites 1,500-step long-horizon actions, up to 100 agents in parallel, and visual coding from design files or web videos; pricing, context window, and API terms are not disclosed. The key point is product shape: not just a model launch, but a bundled model-plus-agent release.

Why it matters: HKR-H lands on the integrated release angle; HKR-K lands on the 1,500-step, 100-agent, visual-programming details; HKR-R lands on the stack-design debate. Missing price, context window, and API terms, plus a commentary source, keep it below p1.

OpenAI News

Retiring GPT-4o, GPT-4.1, GPT-4.1 mini, and OpenAI o4-mini in ChatGPT

OpenAI says it will retire four models in ChatGPT: GPT-4o, GPT-4.1, GPT-4.1 mini, and OpenAI o4-mini. Only the title is disclosed so far; the post does not disclose timing, replacement models, API impact, or migration conditions. The key issue is compatibility breakpoints, not the retirement headline itself.

Why it matters: The official OpenAI post confirms four named models will be retired in ChatGPT, which creates direct workflow and reproducibility concerns for users anchored to specific model choices. HKR-H and HKR-R pass, but HKR-K fails because timing, replacement models, API scope, and migrat

Jan 28Wednesday

Mistral AI

Mistral releases terminal coding agent Mistral Vibe 2.0

Mistral released Mistral Vibe 2.0, a terminal coding agent powered by the Devstral 2 model family. It adds custom subagents, multi-option clarification, slash-command skills, a unified agent mode and automatic updates.

Why it matters: The post lists Vibe 2.0's custom subagents, slash-command skills and subscription entry point, enough to judge how terminal coding agent workflows change.

Jan 27Tuesday

MIT Technology Review · AI

Inside OpenAI’s big play for science

OpenAI launched its OpenAI for Science team in October 2025 to test how GPT-5-class models can support scientists. Kevin Weil said GPT-5.2 scored 92% on GPQA versus GPT-4’s 39%; the piece also notes OpenAI deleted posts that overstated old-paper retrieval as solving unsolved math problems.

Why it matters: Strong HKR-H/K/R: the piece has an insider-angle hook, a concrete GPQA 92% vs 39% data point, and a real tension between scientific ambition and overclaim risk. It stays at 80 because this is reported strategy analysis, not a new model release or shipped capability.

Jan 23Friday

MIT Technology Review · AI

“Dr. Google” had its issues. Can ChatGPT Health do better?

OpenAI launched ChatGPT Health this month, and says 230 million people ask ChatGPT health questions each week. The post says it is not a new model but a wrapper with health guidance and tools, including optional access to medical records and fitness data. The real issue is evaluation: cited studies put GPT-4o at about 85% accuracy on realistic prompts, but only about half of no-choice licensing answers were rated fully correct.

Why it matters: HKR-H/K/R all pass: the story has a strong replacement hook and includes concrete usage plus evaluation numbers. I keep it in the 78–84 band because this is a high-stakes OpenAI product layer, not a new model launch, and rollout, regulatory, and liability details are not fullydis

Jan 12Monday

36Kr (direct RSS)

He Xiaopeng: The best AI companies in the future will build their own chips

He Xiaopeng said XPeng's four 2026 vehicle models will use its Turing AI chip, and Ultra SE and Ultra trims will run a second-gen VLA model for entry-level L4-assisted driving. The post says MAX uses one 750 TOPS chip, Ultra SE uses two, and Ultra uses three; XPeng has entered 60 countries and regions, and VLA 2.0 is already being road-tested in Europe. The real signal is that automakers are pulling chips, models, and deployment in-house as a ceiling-on-performance play, not just a cost move.

Why it matters: The signal is not the slogan but the concrete roadmap: 4 cars, 750 TOPS per chip, 1/2/3-chip trims, and VLA 2.0 road tests. HKR-H/K/R all pass, but this is still a roadmap disclosure rather than a shipped AI-industry event, so it sits at the low end of featured.

Jan 6Tuesday

NVIDIA Blog

NVIDIA RTX Accelerates 4K AI Video Generation on PC With LTX-2 and ComfyUI Upgrades

NVIDIA said GeForce RTX and related devices can run LTX-2 and updated ComfyUI for local AI video generation up to 3x faster with up to 60% lower VRAM use. The post attributes this to PyTorch-CUDA optimizations, native NVFP4/FP8 support in ComfyUI, and an RTX Video 4K upscaling node due next month; LTX-2 open weights are available now and the workflow ships next month. The real signal for AI builders is that local 4K video is shifting from VRAM-bound demos to usable RTX workflows.

Why it matters: HKR-H/K/R all pass: the story has a sharp hook, concrete mechanisms, and clear resonance for local-inference users. I keep it at 76 because this is a vendor-blog ecosystem optimization update, not a major model launch or broad platform shift.

NVIDIA Blog

NVIDIA presents Rubin platform, open models and autonomous driving roadmap at CES

At CES 2026, NVIDIA said its six-chip Rubin AI platform is now in full production and cuts token generation cost to about one-tenth of the prior platform. The post cites 50 petaflops NVFP4 inference for Rubin GPUs, 5x gains from its KV-cache storage tier, and the new open autonomous-driving model family Alpamayo; the key signal is production status and cost curve, not the “AI everywhere” framing.

Why it matters: HKR-H lands because Rubin is in production, not just on a roadmap. HKR-K is strong with ~1/10 token cost, 50 PFLOPS NVFP4, and 5x long-context throughput; HKR-R lands because NVIDIA still sets the tone on inference economics, though the company-blog framing keeps it below 90.

NVIDIA Blog

NVIDIA DGX SuperPOD Sets the Stage for Rubin-Based Systems

NVIDIA introduced Rubin-based DGX SuperPOD systems, with DGX Vera Rubin NVL72 and DGX Rubin NVL8 slated for the second half of this year. One DGX SuperPOD can combine eight NVL72 systems for 576 Rubin GPUs, 28.8 exaflops FP4, and 600TB memory; NVIDIA says inference token cost drops by up to 10x versus the prior generation. The key detail is rack-scale design: 260TB/s NVLink per rack, which the post says removes model partitioning.

Why it matters: This is a substantive NVIDIA infra roadmap with hard numbers: 576 Rubin GPUs, 28.8 exaflops FP4, 600TB memory, 260TB/s NVLink, and up to 10x lower token cost. HKR-H/K/R all pass, but it is still a vendor roadmap post rather than a shipping model or broad product release, so it is

NVIDIA Blog

NVIDIA DGX Spark and DGX Station power the latest open-source and frontier models from the desktop

NVIDIA showed at CES that DGX Spark and DGX Station can run 100B to 1T-parameter models locally on deskside systems. The post cites a 35% average llama.cpp speedup, up to 70% NVFP4 compression, 775GB coherent memory on DGX Station, and a 250,000 token/sec pretraining demo. The real signal is the local dev loop: fine-tuning, inference, RAG, coding assistants, and robotics demos all target replacing some cloud iteration with deskside compute.

Why it matters: HKR-H/K/R all pass: the story pairs a strong desktop-scale hook with concrete specs and demo numbers, and it speaks directly to the local-vs-cloud workflow debate. Still, this is an NVIDIA product post and most performance evidence comes from vendor-run demos, so it stays at 75,.

NVIDIA Blog

NVIDIA DRIVE AV Software Debuts in the All-New Mercedes-Benz CLA

NVIDIA said the new Mercedes-Benz CLA will be the first U.S. vehicle to ship DRIVE AV with enhanced Level 2 point-to-point driver assistance by the end of this year. The post describes a dual-stack design: end-to-end AI for core driving plus a classical safety stack built on Halos, with OTA upgrades, urban navigation, active collision avoidance, and automated parking. The launch timing is specific, but the post does not disclose pricing, sensor configuration, or the exact ODD.

Why it matters: HKR-H lands on the Mercedes CLA deployment hook. HKR-K lands on the disclosed dual-stack design and US launch timing. HKR-R lands on the shipping-autonomy debate, but missing price, sensor suite, and ODD keep it at the low end of featured.

Dec 18, 2025Thursday

OpenAI News

Introducing GPT-5.2-Codex

OpenAI names GPT-5.2-Codex in the headline, but the current RSS item has no body text. The title confirms only the product name and version 5.2; the post does not disclose pricing, context length, availability, or whether it replaces existing Codex. Watch the full post and API docs.

Dec 16, 2025Tuesday

OpenAI News

The new ChatGPT Images is here

OpenAI says the new ChatGPT Images is now available, and the only confirmed fact is a product availability update. The body is empty; the post does not disclose model name, quality, pricing, quotas, or rollout scope.

Why it matters: An official OpenAI launch post makes HKR-H and HKR-R pass: a new ChatGPT image feature is a real product event people will discuss. HKR-K fails because the body here discloses no model name, pricing, quotas, rollout scope, or examples, so it stays near the featured floor.

Dec 11, 2025Thursday

OpenAI News

Introducing GPT-5.2

OpenAI introduced GPT-5.2, and the only confirmed fact in the title is the 5.2 version number. The RSS item has no body, so the post does not disclose model size, pricing, context window, benchmarks, or rollout scope; watch for follow-up API and spec details.

Why it matters: Official OpenAI source plus a flagship model update gives this strong HKR-H and HKR-R, so it clears featured easily. I keep it below the top band because HKR-K fails: only the title is disclosed, with no verifiable specs, benchmarks, pricing, or API changes yet.