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Trump demands data centers generate their own power and pay dividends to communities

On October 21, 2026, Trump posted on Truth Social stating that large new data centers must generate their own power and pay cash "dividends" to their host communities. Related reports noted that the closest existing commitment is the Ratepayer Protection Pledge signed in March of that year by Amazon, Google, Meta, Microsoft, OpenAI, Oracle, and xAI, under which signatories pledged to build or purchase generating capacity and bear infrastructure upgrade costs, though experts believe the pledge may not be enforceable at the federal level. Trump said the dividend proposal goes further than that pledge. Reports on October 22 further stated that Trump also demanded that data centers supply surplus power to local communities free of charge or sell it to them, and noted that communities across the United States have continued to protest AI data center projects over rising electricity prices, noise, water shortages, and other issues. There are currently no facts on subsequent developments.

Porsche and others announce joint construction of a shared data flywheel for autonomous driving

Porsche, Volkswagen Group brands and CARIAD announce the joint construction of a shared data flywheel for autonomous driving development. The news was announced on October 21, 2026 at the NVIDIA GTC Berlin conference, with Porsche leading initial implementation and ecosystem integration, and Voxel51, NVIDIA and Microsoft participating. According to Voxel51, the group's connected fleet generates data each day equivalent to 11,000 ordinary drivers, and the goal of the cooperation is to reduce repetitive real-vehicle testing by up to 90% and shorten AI regression testing cycles by up to 85%. In terms of division of labor, Voxel51 provides the data layer and supports six workflows including multimodal retrieval, automatic annotation and scenario filtering, NVIDIA provides tools such as Cosmos Data Factory and Omniverse NuRec, and Microsoft Azure provides cloud and computing power. The cooperation is currently at the announcement stage, with no subsequent progress disclosed.

eMudhra admits weak private keys can be reverse-engineered with AI assistance

India-licensed certificate authority eMudhra admits that the private keys of its 8 intermediate certificates are all small numbers less than 256, which can be recovered by brute force, and holders could theoretically forge trusted certificates to impersonate websites. Mozilla and Chrome blocked these certificates on October 17, Apple and Microsoft followed suit, and eMudhra revoked the relevant certificates the next day, saying the affected global TLS business accounts for about 1% of its revenue. Researcher Dennis Jackson said an AI agent recovered the private key on its first attempt under a simple prompt, and Mozilla also independently recovered it within hours of receiving the report. CERT-In and CCA have not yet issued public statements on the matter.

Microsoft proposes using Guardian Agents to monitor enterprise AI agents

Microsoft has proposed a plan to use Guardian Agents to monitor and regulate the actions of enterprise AI agents. Hayete Gallot, Executive Vice President of Microsoft's security division, said in a blog post that Guardian Agents should be deployed to monitor and intervene before AI agents execute actions, and stated that frontier models cannot be trusted no matter where they come from. The plan intends to bring enterprise agents under centralized management, assigning each agent an identity, container, and permission policy, then combining identity, data, cloud, endpoint, network, and runtime signals to assess risk in real time, with red team and blue team agents intervening when risk rises. The plan will be implemented through Microsoft's Project Perception security system announced in July. The plan is still at the proposal stage, and there are no public facts about further implementation progress.

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WSJ sees Anthropic's draft IPO filing

The Wall Street Journal has seen Anthropic's draft IPO filing. A report dated October 21, 2026, said the draft showed Anthropic had first-half revenue of $16.3 billion and a book loss of $80.7 billion, with compute commitments of about $450 billion; the draft also disclosed fixed payments totaling $25.2 billion to Google, AWS and Microsoft over the next 7 to 10 years, payable whether or not the capacity is used. A report dated October 22 said the same draft showed first-half revenue of $16.3 billion, up nearly 14-fold year over year, and a net loss of $80.7 billion, of which about $72 billion came from the revaluation of financing instruments such as convertible notes; compute and infrastructure spending in the same period was nearly $9 billion, about 55% of revenue, and forward compute commitments exceeded $600 billion, potentially reaching as high as $750 billion if additional agreements are finalized. There is currently no further progress confirmed by factual evidence.

Microsoft releases multiple new cloud sovereignty tools

On October 21, 2026, Microsoft announced multiple new digital sovereignty features for its cloud services at the Frontier Tour in Paris. Microsoft CEO Satya Nadella and cloud business head Douglas Phillips jointly unveiled a modular cloud sovereignty solution that lets enterprises decide for each computing task the degree of control, transparency, and local execution. A new Sovereign Control Panel aggregates Azure sovereignty signals and will gradually roll out Data Guardian and the Production Touch Ledger, which records remote operations by Microsoft engineers. Azure Managed HSM external key management is now generally available, and on the Azure Local side, DocumentDB, Blob Storage, GitHub Enterprise Local, and Foundry Local have been added. The German Informatics Society (GI) and others criticized such solutions as merely surface-level add-on controls, with the underlying software stack still controlled by U.S. vendors. There have been no further developments so far.

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Microsoft launches security controls for out-of-control AI agents

On October 19, 2026, Microsoft launched security controls for out-of-control AI agents. According to SiliconANGLE, the feature progressively reduces an agent's permissions when its risk score rises: the Discovery tool can identify 60 categories of local agents on employee devices, including Claude Code, Codex, and GitHub Copilot, and assigns each agent a separate identity through Entra Agent ID; Dynamic Agent Risk continuously updates the risk score based on identity, endpoint, cloud, and network signals, and Dynamic Conditional Access uses it to first revoke write permissions, then require human approval, and at the highest level directly isolate or stop the runtime. These features are grouped under Project Perception and Microsoft 365 E7, and Microsoft has not announced availability or pricing. On the same day, Satya Nadella said that he had previously written an article arguing that models should be treated as an internal risk and that security controls should be placed outside the model, and that today Microsoft is putting this principle into practice by extending Project Perception, adding capabilities to continuously assess agent risk, adaptively adjust permissions, and contain threats.

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AuxoAI Completes $20.7 Million Series A Funding

AuxoAI Inc. announced the completion of a $20.7 million Series A funding round led by NTT Venture Capital. The funds will be used to accelerate the company's growth and expand its enterprise AI consulting model. AuxoAI's core platform, Damia, is a toolkit for "forward-deployed engineers" that can turn enterprise data into applications and encode business process knowledge into AI agents capable of long-term collaboration. According to the report, the company has worked with Global 2000 enterprises for more than three years and has established partnerships with platforms such as Google, AWS, Snowflake, Databricks and Microsoft. At present, the only factual development in this event is the aforementioned funding announcement.

LG launches group-wide business review meetings

On October 19, LG launched business review meetings covering all subsidiaries, chaired by Chairman Koo Kwang-mo, to assess 2026 performance and plan for 2027; the meetings will last about one month. According to The Elec, the review will discuss specific business cooperation with Nvidia and Microsoft and follow-up implementation plans, involving AI factories, physical AI, mobility, and AI infrastructure. The report says this is part of LG's "One LG" strategy, aimed at integrating the capabilities of each subsidiary and achieving results in key AI markets. There is currently no qualified factual evidence of further progress.

Microsoft launches security control features for runaway AI agents

On October 19, 2026, Microsoft launched security controls for out-of-control AI agents. According to SiliconANGLE, the feature progressively reduces an agent's permissions when its risk score rises: the Discovery tool can identify 60 categories of local agents on employee devices, including Claude Code, Codex, and GitHub Copilot, and assigns each agent a separate identity through Entra Agent ID; Dynamic Agent Risk continuously updates the risk score based on identity, endpoint, cloud, and network signals, and Dynamic Conditional Access uses it to first revoke write permissions, then require human approval, and at the highest level directly isolate or stop the runtime. These features are grouped under Project Perception and Microsoft 365 E7, and Microsoft has not announced availability or pricing. On the same day, Satya Nadella said that he had previously written an article arguing that models should be treated as an internal risk and that security controls should be placed outside the model, and that today Microsoft is putting this principle into practice by extending Project Perception, adding capabilities to continuously assess agent risk, adaptively adjust permissions, and contain threats.

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Microsoft and City University of Hong Kong propose Taste-Bench to evaluate agent decision-making

Researchers from Microsoft and City University of Hong Kong have built Taste-Bench to evaluate the long-term decision-making capabilities of AI agents on long tasks. The benchmark contains 502 binary-choice questions. According to The Decoder, the best-performing model, GPT-5.6 Sol, achieved an average accuracy of only 59.7%, while GPT-5.5 reached 59.5%. When key clues only become apparent after a large amount of subsequent work, the average accuracy of all models drops to 21%, close to random guessing, and increasing the reasoning budget brings almost no improvement. The researchers also distilled the teacher model's judgments using Qwen3.6-27B as the base model; the student's accuracy on unseen tasks rose from 30% to 47.9%, and its success rate on 41 SWE-bench Pro tasks increased from 14.6% to 33.7%.

View story:Microsoft and City University of Hong Kong propose Taste-Bench to evaluate agent decision-making

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