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2026-11-05

Qwen2026-11-05

Code with CodeQwen1.5

GITHUB HUGGING FACE MODELSCOPE DEMO DISCORD Introduction The advent of advanced programming tools, which harnesses the power of large language models (LLMs), has significantly enhanced programmer productivity and accuracy. Notwithstanding these advancements, dominant coding assistants like Github Copilot, built upon proprietary LLMs, pose notable challenges in terms of cost, privacy, security, and potential copyright infringement. Recognizing the imperative for a more transparent and accessible alternative, the open-source community has embarked on a concerted endeavor to develop open codeLLMs.

2026-10-27

Tencent News · AI Channel22:13

Lex Fridman Podcast Deep Dive | What’s Left for Mathematicians in the Age of AI?

This episode of Lex Fridman was divided into 13 topics. The guests were three: Steven Brunton, who researches fluid dynamics at the University of Washington; Ankur Moitra, who works on theoretical computer science at MIT; and Alex Kontorovich, who studies number theory and Lean at Rutgers University. The video discussed the Navier–Stokes equations, the Riemann hypothesis, and computational complexity theory, prompted by AI’s claims—within just a few weeks—to have solved long-standing open problems in each of these fields. Drawing on their respective areas of expertise, the three mathematicians dissected...

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GeekPark16:42

An agent that helps users snatch up iPhone foldable-screen models is reshaping e-commerce in the AI era.

Shopify AI saw transaction orders grow by a factor of 13. In the early morning of October 16, pre-orders began for Apple’s first foldable-screen phone, the iPhone Duo. Priced from $1,999, initial production capacity was tight, and delivery dates quickly slipped to January next year. This time, it wasn’t just people glued to their screens vying for the launch. This year, Agents have become the strictest “parents” to iPhone Duo scalpers. | Image source: Apple On the MacRumors forum, one user who missed out vented their frustration, while on Reddit others boasted about using Muse bots to snatch up multiple units in a single go—before even a human could click, the inventory had already been swept away by AI. Muse is Meta’s personal Agent, launched on September 8; shortly after its debut, it topped the free charts in the U.S. App Store, with downloads soon surpassing 2.5 million. According to Meta, shopping has become one of Muse’s primary use cases. Around the time the iPhone Duo went on sale, Muse even released a new version optimized for this device, with an update note that emphasized making in‑chat shopping more convenient. AI-driven shopping has moved from demo stages at product launches straight into real‑world stock‑picking scenarios. But not every retailer welcomes these new customers. In late September, Amazon began banning Muse. By October, users of Musk’s Grok Bot encountered the same warning when placing orders on Amazon: unauthorized AI agents continuing to access the platform violates Amazon’s terms of service. Meanwhile, another company, Shopify, took the exact opposite approach. On September 21, Shopify CEO Tobi Lütke announced a deep partnership with Muse, enabling Muse to process checkout through Shop Pay across all Shopify stores. And Shopify’s financial reports already show early returns from this strategy: in the first quarter of this year, orders generated via AI search grew nearly thirteenfold year over year, while store traffic driven by AI increased eightfold. Closing doors on one hand, opening them on the other—when more and more purchasing decisions are handed over to Agents, will the question of “whether or not to let Agents in” become…

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arXiv cs.CL12:00

Conceptizer: Next-Token Prediction Is Not All You Need

arXiv:2610.33027v1 Announce Type: new Abstract: Next-token prediction (NTP) rewards only the token that occurs next, penalizing every alternative. But natural language often offers many ways to express the same meaning. We introduce Conceptizer, a training framework that extends next-token prediction with a reward for meaning. Conceptizer uses a fixed, model-agnostic vocabulary of ~9K concepts, built from contextual synonyms, as units of meaning alongside tokens as units of text. It maps each next-token distribution to a concept distribution and shares the reward for the target meaning across its possible wordings. This provides a concept-level training signal without adding model parameters. Applied to 3 model families at 1B-8B parameters, Conceptizer achieves the lowest held-out NTP perp

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MarkTechPost00:46

Nace AI Releases Drex for Search for AI Agents: 92.05% on BrowseComp-Plus With 12.6 Search Calls

Nace AI has released Drex for Search, bringing its Drex decision models to document search for AI agents. Nace reports 92.05% on BrowseComp-Plus with 12.6 search calls, and fewer agent turns on OfficeQA Pro. The post Nace AI Releases Drex for Search for AI Agents: 92.05% on BrowseComp-Plus With 12.6 Search Calls appeared first on MarkTechPost.

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2026-10-21

NVIDIA Blog18:10

NVIDIA releases an extended version of the Agent Toolkit, empowering enterprises to build trustworthy agents based on private data.

NVIDIA’s open-source Agent Toolkit has added core components such as the Agent Knowledge Foundation, integrating the CUDA-X libraries, the Nemotron Retriever and Kumo series of open models, the OpenShell secure runtime, and the NemoClaw blueprint. This enables enterprises to build specialized agents that are auditable, controllable, and capable of deeply understanding business semantics—without migrating data or modifying existing workflows.

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2026-10-20

MIT Technology Review · AI02:22

Optimizing the internet for AI agents may make it harder for ordinary users to navigate the web.

With the large-scale launch of personal AI agent apps like OpenAI Dots and Meta Muse, AI agents are emerging as the third category of web visitors, following humans and traditional web crawlers. They perform tasks entrusted by real users—such as booking rooms or comparing prices—at machine speed, but because they don’t fit within the existing “human–machine” dichotomy, they’ve been widely blocked by platforms like Pizza Hut, Yelp, and Amazon. If agent traffic continues to grow, websites may shift toward prioritizing AI agents—for example, Shopify has already created a dedicated checkout channel for them—which could lead to worse interfaces, more frequent verification steps, dynamic pricing, and distorted recommendations for human users. The key issue right now is the still‑unsettled regulatory framework: should agents be allowed to enhance consumers’ bargaining power, or should companies be permitted to keep them out?

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2026-09-14

OpenAI 官方新闻2026-09-14

Perplexity trusts GPT-6 Astra with end-to-end systems

Perplexity uses Astra to write communications, change software, and monitor production systems, and checks in much less frequently than with earlier models.

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