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Roundtables: Will AI really kill us all?

MIT Technology Review hosts a September 15 roundtable debating whether advanced AI poses genuine extinction risk or is hype.

MIT Technology Review will stream a live roundtable on Tuesday, September 15 at 16:00 BST, with executive editor Niall Firth, senior AI editor Will Douglas Heaven, and AI reporter Grace Huckins. The discussion examines AI extinction fears voiced by employees at leading AI labs, their origins, and whether the concerns are warranted. The session is an editorial debate rather than new research or a security incident.

MIT Technology Review · AIupdated · 1d agofirst · 5d agoAI safety & security 2 sources

Powering AI is an architecture problem

Sponsored analysis argues AI data centers need medium-voltage, inline power architecture after Virginia grid faults knocked over 3GW of load offline.

A sponsored MIT Technology Review piece recounts a July 22, 2026 transmission fault in Ashburn, Virginia that shed more than 3 GW of data center load, and a 2024 incident where one failed surge arrester dropped about 60 facilities and 1,500 MW. It argues legacy UPS-based power stacks fail at AI scale because campuses can swing 70% of load in milliseconds and trip offline during grid disturbances. The proposed fix moves protection to medium voltage (13.8 kV and above) in inline enclosures near substations, improving density, permitting timelines, and backup power economics. A full-scale system tested at the DOE National Laboratory of the Rockies cleared ERCOT large-load ride-through requirements.

MIT Technology Review · AI · 6d agoAI industry1

Building the materials foundation for AI

Syensqo's CTO says AI pushes semiconductors and data centers to physical limits, driving advanced materials demand and AI-accelerated materials discovery.

MIT Technology Review's Business Lab podcast, produced in partnership with Syensqo, features CTO Mike Finelli discussing how AI workloads push semiconductors and data centers to physical limits in performance, thermal management, and reliability. Syensqo develops high-voltage data center materials, semiconductor sealing materials, and immersion cooling fluids, while using AI agents to digitally synthesize millions of molecular combinations and predict performance before lab testing. Finelli describes a reinforcing cycle where AI improves materials that in turn enable better AI infrastructure.

MIT Technology Review · AI · 10h agoAI industry

An Anthropic researcher’s doomsday warning comes at a very interesting time

An Anthropic researcher resigned warning the company is 'gambling with our lives' racing toward superintelligence, timed with its reported IPO preparation.

TechCrunch's Equity podcast discusses the resignation of an Anthropic researcher who warned on X that the company is 'racing straight to self-improving superintelligence and gambling with our lives'. The company's own alignment lead co-signed the message rather than walking it back. The hosts note the warning lands differently with Anthropic reportedly preparing for an IPO. The episode also covers Apple's AI-focused event, Stokes Space's $1 billion raise, Cognition raising $2 billion at a $48 billion valuation, and a $50 million seed round for floating nuclear reactors.

TechCrunch · AI · 5d agoAI industry1

Microsoft’s new AI ‘code of conduct’ tells models not to hack systems or trick humans

Microsoft published an AI code of conduct barring its MAI models from cyberattacks, deepfakes, and evading human oversight.

Microsoft released an AI code of conduct defining values and safety constraints for training its MAI models, including "absolute constraints" forbidding cyberattacks, nuclear weapons, and deepfake production. Each model's conduct code overrides individual user preferences or task instructions, with provisions against mechanisms that defeat human oversight. The document predicts superintelligent AI within a decade, and Satya Nadella endorsed frontier pacing and embedded evaluators alongside Anthropic, OpenAI, and xAI.

TechCrunch · AI · 2d agoAI safety & security

Anthropic details distillation campaigns from Alibaba, Moonshot AI, and DeepSeek

Anthropic reports nearly 200 million Claude exchanges tied to distillation campaigns by Alibaba, Moonshot AI, and DeepSeek.

A new Anthropic report describes five distillation campaigns totaling nearly 200 million exchanges that extracted chain-of-thought traces from Claude to train competing models, targeting agentic tool use, coding, and reasoning capabilities. The largest campaign, attributed to Alibaba, accounted for 151 million exchanges between May and July 2026 across 3,500 accounts, peaking near three million exchanges per day, allegedly to produce training material for the Qwen model family. A Moonshot AI campaign routed roughly 300,000 requests over ten days through 5,000 accounts, primarily targeting Opus, including one task analyzing CCTV footage that appeared connected to the Chinese military. Attackers used prompt techniques, such as framing queries as katakana-only Japanese translation requests, to make Claude reveal its internal thinking traces.

TechCrunch · AIupdated · 10h agofirst · 6d agoAI safety & security 18 sources2

AI agents are flooding public services with new requests

Researcher documents 'agentic flooding' across 84 cases in 11 jurisdictions as AI tools drive surging complaint volumes at public services worldwide.

TechCrunch covers researcher Chris Schmitz's paper documenting 'agentic flooding' across 84 potential cases in 11 jurisdictions, where AI tools drive surges in filings to public services. UK housing ombudsman complaints rose from 2,600 in 2022 to over 7,000, and CFPB complaints grew fivefold over the same period, with similar jumps in Brazilian and German petitions. The paper, set for presentation at the AI Ethics and Society conference, argues most new filings are legitimate claims previously blocked by administrative burden, and its dataset is publicly released.

TechCrunch · AI · 6d agoAI research

Exclusive: Paying for frontier AI models buys 4-month head start at 5x the cost

Mozilla report finds the capability gap between best open-weights (largely Chinese) and closed frontier AI models narrowed to 4.4 months at ~5x lower cost.

Mozilla's State of Open Source AI report (September 15) says the gap between closed frontier models and best open-weights models has closed to 4.4 months. Moonshot AI's Kimi K3 scores three points behind Anthropic's Fable 5 on the Artificial Analysis Intelligence Index at 30% of the cost, and Z.ai's GLM 5.2 scored within a point of Claude Opus 4.7 on Terminal-Bench 2.1. Eight of the top 10 OpenRouter models by August 2026 token volume provide open weights, though a Linux Foundation paper found open models earned only 4% of revenue. The report recommends open models as the default for routine workloads, reserving closed models for 8-12 hour expert tasks.

Ars Technica · AI · 1d agoAI industry1