When you purchase through links in our articles, we may earn a small commission. Tapo's 4K solar security camera kit hits a new low price at Amazon The solar-powered Tapo C660 is on sale for $115.99, down from $169.99. If you've always wanted an outdoor security camera for your home but dreaded the wiring, the battery upkeep, or the paid subscriptions for storing footage, then here's a deal for you. My favorite thing about the C660 is how easy it is to set up. Get up on a ladder, drill a couple of screws into where you want it mounted, actually mount the thing, and you're done.

Anker has turned up to IFA with MindBase, an AI-powered local home hub built to sit at the heart of your autonomous home. Essentially, it's a NAS with a 64GB SSD and two bays to hold either 2.5 or 3.5-inch hard drives, with its own AI compute built on top. Anker is selling it as a way to both run your smart home and store your family's treasured memories, and as a digital security guard. If you want MindBase to watch your home, then you'll need to invest in Anker's lineup of home security cameras. That includes the new Eufy Video Doorbell S4, Window Camera E10, Fall Detection Sensor or just its range of plain ol' pan-tilt-zoom cameras.

The new product lineup includes several additions in security cameras. The Eufy NVR Security System E50 is a multi-camera system that has a hybrid 2K fixed bullet and 4K PTZ dual-lens design. It also uses the brand's OmniTrack AI tracking system and auto-framing. It is available now for buyers in the US, Canada and Australia, with the four-camera kit starting at 999 and the eight-camera option starting at 1,599. The Eufy Video Doorbell S4 is both a wired video doorbell and security camera that offers 9 MP resolution.

Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Look Up Say More Switch Off Creator Playbook Mashable Voices Trending Now Mashable Selects Safety Net Versus Gift Ideas For Everyone On Your List In My Bag All Series Governor Greg Abbott was previously criticized by his Democratic challenger for funding Flock cameras. Backlash against Flock has led to the state of Texas pausing funding on the AI cameras. Flock's AI surveillance cameras are increasingly being targeted by its critics across the country. No, we're not just talking about vigilantes who are taking the cameras down in their towns. And it's a bipartisan effort; an anti-Flock position is being taken up by both Republican and Democratic politicians.

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The first anti-AI protester to be jailed has a message for OpenAI, Anthropic and Meta: 'Regain your humanity' Wynd Kaufman, 69, chained and locked the front doors of OpenAI's headquarters last year with members of StopAI A n activist who blocked the entrance to one of the world's biggest AI companies is believed to have become the first person jailed for protesting against artificial intelligence as supporters dub her the "Rosa Parks of AI risk". Wynd Kaufman, 69, surrendered herself on Friday to authorities in San Francisco . She was found guilty by a jury for her role in an action last year that saw members of the group StopAI chain and lock the front doors of OpenAI's headquarters in protest against the pursuit of artificial superintelligence. The retired teacher from Berkeley, California, refused to move from a sit-in protest in February 2025 and pleaded not guilty to multiple misdemeanor charges. She was convicted in June of interfering with a business, trespassing with intent to interfere with a business, unlawful assembly and refusal to disburse a riot.

Sotheby's Big Auction Raises Concerns Hype and Wealth Are Upending Science Private buyers are increasingly outbidding museums for fossils. That's making it difficult--or even impossible--for researchers to improve our understanding of the past. Forget the sale of the century. The auction house Sotheby's is gearing up for the sale of the epoch. On July 14 it will open live bidding on assorted fossils, but the pièce de résistance is lot 20, a rare 67-million-year-old skeleton.

If you want to beef up your home security this Prime Day, Eufy's Floodlight Camera is a great way to do it. There are tons of great outdoor security cameras, but my favorite floodlight security camera outshines them all. It combines a clever dual-lens camera design with two bright light panels capable of illuminating your backyard or driveway. It can also track suspicious characters and record locally, so there's no need for a subscription. It occasionally drops in price, but it's currently at the cheapest price I've ever seen it.

In enterprise settings, organizational data is segregated, siloed and carefully protected by elaborate access control frameworks. These access control structures can completely break down if an LLM fine-tuned on the siloed data serves requests, for downstream tasks, from individuals with disparate access privileges. We propose Permissioned LLMs (PermLLM), a new class of LLMs that superimpose the organizational data access control structures on query responses they generate. We formalize abstractions underpinning the means to determine whether access control enforcement happens correctly over LLM query responses. Our formalism introduces the notion of a relevant response that can be used to prove whether a PermLLM mechanism has been implemented correctly. We also introduce a novel metric, called access advantage, to empirically evaluate the efficacy of a PermLLM mechanism. We introduce three novel PermLLM mechanisms that build on Parameter Efficient Fine-Tuning to achieve the desired access control. We furthermore present two instantiations of access advantage-(i) Domain Distinguishability Index (DDI) based on Membership Inference Attacks, and (ii) Utility Gap Index (UGI) based on LLM utility evaluation. We demonstrate the efficacy of our PermLLM mechanisms through extensive experiments on five public datasets (GPQA, RCV1, SimpleQA, WMDP, and PubMedQA), in addition to evaluating the validity of DDI and UGI metrics themselves for quantifying access control in LLMs.

The text produced by language models (LMs) can exhibit specific'behaviors,' such as a failure to follow alignment training, that we hope to detect and react to during deployment. Identifying these behaviors can often only be done post facto, i.e., after the entire text of the output has been generated. We provide evidence that there are times when we can predict how an LM will behave early in computation, before even a single token is generated. We show that probes trained on the internal representation of input tokens alone can predict a wide range of eventual behaviors over the entire output sequence. Using methods from conformal prediction, we provide provable bounds on the estimation error of our probes, creating precise early warning systems for these behaviors.