AI News

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Hugging Face and Pollen Robotics Open Pre-Orders for the $399 Microduck

Hugging Face and its Pollen Robotics subsidiary opened pre-orders on 27 August 2026 for Microduck, a 25 cm bipedal robot duck priced at $399 before taxes and shipping, with first deliveries targeted before Christmas 2026. The machine carries 15 motors, a wide-angle camera, an 8×8 time-of-flight LiDAR array, two IMUs and an articulated beak that works as a gripper, on a Rockchip RK3566 with 1 GB of RAM and 32 GB of storage running its neural policy at 50 Hz. Seven behaviours ship on the device — walking, rolling on skates, grasping, kicking, standing up after a fall, sitting and a generated audio identity — and every one was trained in MuJoCo with proximal policy optimisation and transferred to hardware. The control stack and the full training pipeline are published under Apache 2.0, but the hardware is not open and Pollen Robotics says it has no plans to change that. This breakdown covers the pack pricing, the complete published specification, the Open Duck Mini project the design grew out of, how it compares with the Reachy Mini line, and the battery, payload and compute ceilings that decide who should actually buy one.

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Google Releases Omni 1.1 Flash Video Model With 1080p and 4K Support

Google released Gemini Omni 1.1 Flash on 27 August 2026, the production version of its generative video model, and the headline change is output above 720p. The model now accepts resolution values of 360p, 720p, 1080p and 4K, extends an existing clip in ten-second increments to a cumulative forty seconds, and interpolates footage between a start frame and an end frame you supply. It is paid-tier only, billed on output tokens at a rate Google states as 5,792 tokens per second of 720p video — roughly $0.10 per second — with a 360p draft tier at a third of that cost and up to 60% faster. This breakdown covers exactly what shipped, why the 1080p and 4K figures are documented as upscales rather than native renders, how the token billing compares against Veo 3.1, which surfaces the model is live on today, and the limitations list that blocks editing uploaded video for users in the UK, the EEA and Switzerland.

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Google Brings Trip-Planning Features to Search’s AI Mode

Google has added flight price tracking, conversational hotel booking and miles-and-points pricing to AI Mode, the conversational surface inside Search. Announced on 27 August 2026, the three features complete a nine-month build that started with the Canvas itinerary panel in November 2025 and turns AI Mode from a place where you research a trip into a place where you arrange one. The rollout is far more uneven than the headline suggests: price tracking reaches more than 180 countries and the points display is global, but hotel booking is live in a single country, in English, with ten named partners including Booking.com, Expedia, Marriott and Hilton. This breakdown covers exactly what shipped, where each feature actually works, what Google’s own usage data says about why travel was the obvious target, and what the shift does to the travel websites that used to be the destination.

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Visa Ships a Security AI That Patches Your Code Before Any Human Reviews It

Visa has open-sourced the Visa Vulnerability Agentic Harness, the tooling it used to hunt for bugs across its own payment network, and its documentation contains a line worth pausing on: “A plain scan edits your code.” In its default configuration the harness runs discovery, remediation and validation end to end, writing candidate fixes straight into source files before any person has looked at the finding or the patch. Nothing reaches production without a human, but nobody approves the patch before it is written. This breakdown covers the four-phase, eleven-stage pipeline, exactly where the “no human review” claim holds and where it collapses, what Visa itself says about oversight, and the independent evidence that only 26% of AI-generated security patches fix the flaw without changing what the software does.

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Meta Reportedly Abandoned an AI-Focused Restructuring Plan That Would Have Laid Off Thousands

Project OT — short for Organization Transformation — was Meta’s plan to make the company “AI native” by handing much of its routine work to software agents, leaving small “talent-dense” pods of humans to supervise them. A Reuters special report published on 26 August 2026 says the plan was drawn up at Mark Zuckerberg’s Hawaii compound in January, modelled team cuts of up to 60 per cent, and was abandoned in part on the evening of 19 May, hours before the first wave of notices went out. This breakdown covers what Project OT actually was, the pod and village structure it introduced, the internal metrics that undermined it, the keystroke-tracking software that triggered an employee revolt, the 8,000 layoffs and 7,000 redeployments that did happen, and what any organisation writing an AI workforce plan should take from it.

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Anthropic to Pay Nscale $45 Billion for Power and Nvidia Vera Rubin Chips

Nscale has agreed to sell Anthropic roughly $45 billion of AI computing capacity over six years, according to Bloomberg and CNBC reporting on 26 August 2026. The capacity amounts to about 460 megawatts at a West Virginia campus, fitted out with Nvidia Vera Rubin systems arriving from late 2027. This breakdown covers the reported terms, what 460 megawatts actually means, who Nscale is and how a $45 billion contract reshapes its September listing plans, the Monarch Compute Campus and its off-grid gas microgrid, the Vera Rubin generation-on-generation numbers, where the deal sits alongside Anthropic’s Google, Broadcom, Amazon, Microsoft and SpaceX commitments, the price per megawatt-year, the risks nobody is pricing, and what any of it means for organisations that buy AI rather than build it.

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QueryStory Wants You to Believe What AI Is Telling You: Inside Its $6M Bet on Verified Answers

QueryStory came out of stealth on 26 August 2026 with a $6 million seed round from Brightmind Ventures and New York Life Ventures at a $60 million valuation, and an unfashionable pitch: the problem with enterprise AI analytics is not speed, it is that nobody can tell whether the answer is true. This breakdown covers CEO Shapor Naghibzadeh’s route from Google’s Operation Aurora war room through six years of security tooling to co-founding Chronicle in Google X Labs, the founding team alongside CTO Stanley Yang and CPO David Glusic, the four mechanisms the platform is built on — SQL that surfaces automatically, an explicit confidence indicator, human review recorded in the platform, and narrative assembly that refreshes as the data moves — the argument against consumption-priced frontier-lab tools, TechCrunch’s hands-on test that produced in a few hours a space-activity visualisation that once took several weeks with a developer, the arithmetic of a $6M round at a $60M valuation, a due-diligence table for anyone evaluating AI analytics, and the four questions the launch leaves genuinely unresolved.

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