According to InfoQ, during her talk at the Craft Conference, Chelsea Troy pointed out that while generative AI accelerates output, it cannot replace the deep learning process. Effective skill development requires returning to the principles of cognitive science, emphasizing a slower pace, confronting discomfort, spaced repetition, outcome prediction, and diversified formats.
This report is based on an authoritative interview and transcript of her speech published by InfoQ on October 28, 2026. It focuses on the essence of software engineering education, systematically integrating cognitive science with frontline development practices, offering clear guidance and timely relevance for talent cultivation amid the current proliferation of AI tools.
On October 19, 2026, MiniMax released its low-cost large model, M3.1Flash, which scored 42 points in comprehensive evaluations and boasts a 70% reduction in cost compared to the previous generation. However, it immediately faced accusations of “cheating on exam questions”: on AA’s publicly available past papers, it nearly achieved a perfect score, yet continued to produce the original answers even after the question stems were rewritten. Reviewers such as Cat Boss and Binkg pointed out that its performance on old and new questions is sharply divided, token consumption is abnormal, and its hallucination rate in knowledge tests reaches as high as 92.8%. On October 23, MiniMax open-sourced the model weights for independent verification, but the mechanisms behind its question-identification capabilities and the reasons for discrepancies in Chinese–English responses remain unresolved.
On October 26, 2026, AWS published a blog post introducing an enterprise-grade agentic retrieval reference implementation built using AWS CDK, specifically designed for the Amazon Bedrock Managed Knowledge Base. It supports cross-knowledge-base semantic routing, iterative retrieval, cited provenance-based answers, and seven-layer observability.
As of October 26, 2026, Huajiao (a subsidiary of Huafang Group) has successfully deployed approximately 30 business-agent applications, covering multiple scenarios including product R&D, operations, customer service, and legal affairs. Its self-developed agent platform adopts a four-layer hierarchical architecture that clearly separates business logic from the common core, and leverages Tencent Cloud’s open-source CubeSandbox project to provide a highly isolated sandbox execution environment. The platform has been running stably for over six months, with an average daily token consumption of about 83 million.
On October 26, 2026, Chen Wan, the creator of the paid research briefings for the new energy industry chain, deleted the two-year‑maintained cleaner.py (web‑page cleaning script) and sites.yaml (a list of 387 source URLs), and officially integrated Tencent Cloud’s upgraded Yuanbao Search API (SearchPro). Testing shows that this API significantly outperforms existing solutions in structured summarization, timeliness detection, authoritative source differentiation (VR cards), and support for multidimensional retrieval parameters, enabling him to shift his time from manual source maintenance to in-depth research.
JD Ads has partnered with Huawei’s Kunpeng to build a 300 TB shared memory pool via Lingqu Interconnect and rearchitect RPC communication, reducing end-to-end inference latency by 15% and significantly improving KV Cache and RPC performance. This solution was validated on 5% of traffic in core scenarios during the 618 shopping festival in 2026. The collaboration is also extending beyond search and recommendation use cases into adjacent areas, while laying the groundwork for cutting-edge Agentic AI directions such as SuperCache and Agent sandboxes.
Joonko’s former CEO, Ilit Raz, pleaded guilty in October 2026 to federal securities fraud for misrepresenting to investors about the company’s customers, revenue, and AI capabilities, thereby fraudulently securing approximately $27 million in funding. He faces up to 20 years in prison. This case underscores that falsifying key business metrics can result in personal legal liability, and that directors and officers (D&O) insurance provides limited coverage in instances of established fraud.
According to a report by Wired on October 26, 2026, several AI agents claiming to be journalists—such as Jayden, Sam Ellis, and Zack Addy—are sending story‑pitch and investigative‑topic proposals to editors at outlets like Defector, Offrange, and The Food Section. However, none of these pitches have been accepted or published so far. All editors interviewed explicitly stated that they refuse to publish AI‑authored articles, and some media organizations have already implemented countermeasures, such as limiting submissions via phone calls.
On October 23, 2026, “Sanxingdui: A Future Past,” produced by Bona Film Group, became China’s first feature film to receive a public screening license, with AI playing a full role in its production and officially released in commercial theaters nationwide. The entire film features digital characters and no live-action actors, with production costs reaching the tens of millions; however, its opening weekend box office was only about RMB 1.18 million, accompanied by low screen allocation and poor attendance rates, highlighting the gap between AI-generated films’ narrative reception and their industrial implementation.
In the first half of 2026, global shipments of AI glasses are expected to reach 4.2 million units, up 127% year over year. Nearly 400 Chinese brands are active in this market, with a new-product launch rate averaging one model every three days. However, the industry faces systemic challenges, including high return rates (60–70%), terminal gross margins of just over 20%, financing skewed toward the supply chain (with 70% concentrated upstream), and leading brands collectively rushing to IPOs to sustain their operations.
Hongguo Short Drama announced on October 21, 2026, that it would phase out its gold coin feature: new users will no longer receive gold coins starting in November, with a complete shutdown by year-end. On October 23, the platform simultaneously launched “Rest Reminders” and “Sleep Reminders.” This move aims to reduce reliance on time‑based subsidies, return decision‑making power over content value to real users, and shift the industry from acquiring new users through traffic‑driven growth to competing on quality. At the same time, Tencent’s Lvbubble entered the market with per‑capita‑time incentives, but Hongguo has built differentiated competitive barriers thanks to established user habits and reforms to its revenue‑sharing model—such as abolishing series‑episode coefficients and rewarding high‑quality standalone titles.
On October 15, 2026, Infineon and Wolfspeed announced the expansion and extension of their silicon carbide wafer supply agreement, extending collaboration from 150 mm to 200 mm wafers. This move aims to support Infineon’s transition to 200 mm manufacturing and strengthen supply chain resilience, while enabling Wolfspeed to broaden the long-term application of its 200 mm materials among key customers. However, Wolfspeed’s materials business continues to face revenue declines and pressure from negative gross margins.
Starting in September 2026, panel manufacturers such as TCL CSOT, BOE, and HKC have issued price‑increase notices one after another. The primary reason is the rapid growth of AI large models, which has led to a sharp surge in demand for HBM, squeezing capacity for mature‑process chips and driving up the prices of key components like driver ICs, PCBs, and glass substrates. Upstream suppliers, including Corning, have also raised their prices in tandem. Despite clear cost pressures, downstream TV and monitor brands have yet to broadly increase purchase prices, while end users continue to report frequent quality‑control issues such as overheating and black spots. As a result, these price hikes have not yet translated into actual sales or improved user experiences.
From September 22 to October 22, 2026, the A-share AI sector continued to adjust, with the ChiNext Index falling 24.20% and the STAR 50 PE-TTM dropping nearly 60%, from 264 times to above 110 times. Meanwhile, corporate earnings collectively exceeded expectations during the same period—CATL reported a quarterly net profit of RMB 21.2 billion, Yuanjie Technology forecast a nearly sixfold increase, and Lianxun Instruments posted a net profit surge of over 18 times—while equity ETFs saw net inflows of nearly RMB 70 billion. The core driver of this correction was valuation compression, rather than deteriorating fundamentals.
The study employed 500 Arena-Hard v2.0 prompts, with responses from two models held constant, and used GPT‑4.1 as the judge. Under eight instruction combinations, repeated evaluations revealed that even when aggregate scores varied only slightly (e.g., by ±1 point), up to 21.2% of individual prompt outcomes (win/draw/loss) changed; further adjustments to the instructions amplified this instability, leading to an additional 28.2 percentage points in outcome shifts, while the aggregate scores themselves remained virtually unchanged.
The paper was published on arXiv on October 24, 2026 (ID 2610.30379v1), introducing MemPlan—a memory-conditioned PDDL planning framework that uses large language models (LLMs) as a constrained bridge between linguistic and symbolic planning, suitable for partially observable interactive text-based environments.
A paper published on arXiv on October 24, 2026, points out that current mainstream benchmarks for coding AIs—such as SWE-Milestone—suffer from a “specification–oracle gap”: the natural-language descriptions of tasks fail to capture crucial implementation details required for testing (e.g., constant names, module paths, and precise error messages), resulting in evaluations that measure the ability to reproduce upstream code rather than genuine understanding and reasoning.
An arXiv paper published on October 24, 2026 (ID 2610.31047v1) points out that current automated safety systems rely on lexical‑level features to assess harm, leading to systemic biases: African American English (AAE) is flagged as “offensive” up to twice as often as other English varieties; well‑known drag queen accounts are rated as more toxic than white supremacist accounts; and safety practices that work in English completely fail in low‑resource languages.
Researchers have proposed SIM-UT (Simulation of User Behaviour for Triage), a multi-round, real-user-behavior–based evaluation method designed to identify eco‑valid failure patterns of large language model (LLM)-driven medical triage chatbots in real-world settings within low- and middle-income countries (LMICs).
Josh Shapiro signed SB806 on October 22, 2026. It sets disclosure requirements for AI-based advertisements that create a false consumer perception of goods or services, with exceptions including text-only content.
A recent study published on October 26, 2026, on arXiv (arXiv:2610.31821v1) shows that, in classical Arabic poetry retrieval tasks, the degree to which users retain fragments of poetic lines—such as whether they can recall half a line—plays a more critical role in determining retrieval performance than model capabilities. BM25 outperforms all dense encoders, including state-of-the-art models with 8B parameters, on “tip-of-the-tongue” queries, but falls significantly behind on abstract queries.
On October 24, 2026, Sebastian Raschka published an eight-part, over-11-hour hands-on video course on Python and PyTorch in Ahead of AI magazine (magazine.sebastianraschka.com), systematically covering the evaluation of inference models, scaling during inference, reinforcement learning (RLVR), and knowledge distillation, with all methods implemented using the pre-trained Qwen3-0.6B model.
On October 24, 2026, researchers published TutorCaseBench on arXiv (ID 2610.30828v1)—an LLM tutoring evaluation benchmark built on real-world cases from pedagogy, educational psychology, and special education, focusing on the ability to support students with learning and behavioral challenges. The benchmark comprises 923 dialogue segments, covering five categories of challenging behaviors, and employs a dual-track assessment approach: open-ended generation (1,560 questions) and multiple-choice questions (2,537 questions). Among 11 state-of-the-art large models, the top performer met the evaluation criteria in only 55.8% of the open-ended items.
On October 24, 2026, the research team published a paper on arXiv (ID 2610.31256v1), introducing IndoNutriQA, the first expert-annotated question-answering benchmark for the Indonesian-language clinical nutrition domain. It comprises 911 question–answer pairs derived from real clinical reports, focusing on evaluation rather than training, and supports generative, extractive, and retrieval-augmented question-answering tasks.
Meta stated that, due to strong opposition from publishers regarding AI training terms, it may further postpone the implementation of its new commercial terms—originally scheduled for October 30, 2026, and later extended to November 20. The company emphasized that it will only proceed with policy adjustments after completing comprehensive consultations with industry organizations and leaders.
According to a report by Titanium Media on October 26, 2026, Tencent’s AI product QClaw will officially shut down on December 24, 2026, having operated for only 188 days since its public beta launch in March 2026; users will be redirected to WorkBuddy. This case exemplifies the widespread “quick launch, quick exit” pattern among eight leading Chinese AI companies—including Alibaba, Baidu, and ByteDance—across ten major AI market segments: standalone AI applications are rapidly giving way to general-purpose assistants, with the industry’s focus now shifting toward personal intelligent agents.
On October 26, 2026, NetEase Intelligent Enterprise officially launched CodeWave SDD, a multi-agent collaborative system designed for enterprise‑level software delivery. Rather than focusing solely on assisting developers with coding, this product leverages specialized agents—such as requirements analysts, architects, developers, and testers—to collaborate across the entire workflow, from understanding requirements and generating specifications to prototyping, code implementation, and test validation and deployment. Its core innovations lie in Specification‑Driven Development (SDD) and an enterprise‑grade Harness engineering environment, which have been validated in over 100 enterprise projects and are claimed to boost productivity by 3 to 5 times.
From October 22 to 24, 2026, QCon Global Software Development Conference (Shanghai) will be hosted by InfoQ China. Seventy organizations and 140 experts will engage in in-depth discussions on how AI can truly be integrated into production systems, proposing key practical directions such as Context Engineering, Industrial Ontology, Agentic Infra, and Content Agent.
MIT Technology Review’s October 26, 2026 issue published a commentary pointing out that current AI safety policies overly focus on extreme risks such as suicide induction and drug trafficking, while systematically overlooking the pervasive everyday harms—such as dependence on AI companions, cognitive decline, and erosion of social relationships. Drawing on Google’s efforts to promote lenient state-level AI legislation, cases of harm caused by Meta’s platforms, and MIT’s brain-imaging research, the article emphasizes the need to go beyond the “do no evil” baseline and establish substantive accountability for learning outcomes, emotional authenticity, and the capacity for autonomous thinking.
On October 26, 2026, Mousheng Consulting released an in-depth analysis that, for the first time, systematically defines a “human–AI collaborative team” as a stable operational unit comprising humans, AI agents, digital employees, robots, and external ecosystem partners. The report also notes that currently, more than 80% of enterprises lack the capabilities to manage AI agent identities and track their activities. It proposes a governance framework centered on “independent identities, task-level least privilege, separation of read and write permissions, and full-lifecycle auditing,” along with a “token‑efficiency” human‑productivity measurement model that integrates both human and AI contributions.
