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frame in MiniMax gives fantastic results (Activity: 2263): A user shared a MiniMax-H3 LoRA for generating locked-subject 360° orbit shots from first/last-frame conditioning: pablodawson/MiniMax-H3-360-Orbit-LoRA. The prompt explicitly constrains the scene to a frozen instant—no object/pose deformation, no drifting, no continued action—so that camera parallax is the only motion source, targeting cleaner pseudo-volumetric outputs suitable for downstream reconstruction workflows. A linked Reddit de

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all, it’s easy to forget that AI has already been life-threatening to some, not through bioweapons, but psychologically. For example, Character.AI settled several wrongful death lawsuits earlier this year brought by families of underage users who died by suicide after interactions with its bots. Multiple families have also sued OpenAI over ChatGPT’s alleged role in their loved ones’ suicides and delusions. Making AI safer across languages and cultures is the mission of Circuit Breaker Labs, one

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nt button's action when pressed on a view drawn before Claude Code restarted; Fixed a plugin's pane showing nothing when one Code element held a diff that does not parse; it now draws as plain code; Fixed plugin LSP servers receiving literal ${user config. } and ${CLAUDE PLUGIN ROOT} placeholders in initializationOptions and settings instead of substituted values or manifest defaults; Fixed a plugin's tool.call hook making Bash fail and file searches read the wrong folder in subagents that run i

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Innovation Artificial Intelligence AI slop is everywhere, and it's getting harder to tell what's real. These tips and tools can help. AI images have subtle flaws that reveal they’re fake; Check faces, hands, and textures for common AI errors; Free tools like Circle to Search help detect AI images AI-generated images are everywhere now. I see them in my news feeds, in Google Images, in Pinterest pins, and even in some ads. They’re so pervasive that people have coined the term “AI slop.” Sorry to

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iptions announced in June, though those still rely on footage Why it matters: Security cameras sell on footage you can replay, share, or hand over, and that same footage is what draws the privacy worry. A camera that physically can't capture video would sidestep much of that and fit Apple's privacy pitch. What remains to be seen is whether a text description can be enough if something actually goes wrong. TOGETHER WITH GRANOLA 🗓️ Your meetings, now in Claude The Rundown: Granola is the AI notepa

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PDF and a JSON schema. The system returns JSON, which is scored value by value against a gold file. The code is on GitHub, and the data is on Hugging Face under CC BY 4.0. The 4 flaws it targets Datalab’s launch post names 4 recurring problems with existing extraction benchmarks: Bias: documents and scoring can favor the vendor that built the benchmark; Opaque harnesses: a low score may reflect a broken harness, not a weak model; Unclear scoring: readers cannot tell why a given document scored l

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ni. She accused HCA of routinely deleting data the tool uses to create schedules, which prevented auditing how well it worked and she claimed may have violated several healthcare laws. (HCA has yet to formally respond in court, and Russell declined to comment.) Timpani was built on Palantir Foundry, a software platform for storing and analyzing different data from across a company’s operations. Named after the beat-keeping musical instrument, it uses algorithmic forecasts of patient volumes and

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alid evidence, or did it make incorrect assumptions? This is why I recently left my position at Google DeepMind. I believe we need a fresh approach to machine reasoning—one that draws on AlphaGo’s architecture. AlphaGo maintains a record of what it knows about a given position: the game tree. This data structure contains all the variations, the possible futures, that AlphaGo has considered, each move and position being annotated with judgments made by its neural networks. As its reasoning progre

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choice—and these are powers that today’s AI lacks. This is why I recently left my position at Google DeepMind. I believe we need a fresh approach to machine reasoning, one that draws on AlphaGo’s architecture. Here’s why today’s AI doesn’t really reason—and what it would take to change that . Thore Graepel is chair of machine learning at University College London. He was a core member of the AlphaGo team at DeepMind. The must-reads I’ve combed the internet to find you today’s most fun/important

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that queries and prepares data where it resides, without migration or centralization—can convert raw data estates into intelligence that AI agents can act upon. As data residency laws, multicloud environments, and structural complexity make centralization increasingly impractical, sovereign control over where models run and data lives is what keeps that adaptability intact. Download the report. This content was produced by Insights, MIT Technology Review’s custom content arm, not its editorial s

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orms for it since launching in 2023. Suno is just throwing its hat into the ring — likely in an attempt to diversify the platform, given its music generator has attracted so many lawsuits . Pairing AI music with generated voices is Suno’s spin on text-to-speech tools. It’s optional, meaning you can easily turn off the background music with a toggle if you just want clean speech, but the idea is that it’ll compliment certain use cases for generative spoken word — such as having a calming soundtra

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reasons. There’s no seat belt equivalent for AI, no straightforward solution that can demonstrably reduce risk overnight. (It also took decades for the majority of states to pass laws mandating that people actually wear them.) The potential harms are less certain and less quantifiable. AI doomers will tell you the technology could result in human extinction in a decade; skeptics argue that’s sci-fi marketing malarkey. We’ve talked about various AI risk scenarios before, but no one can say for ce

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CrewAI does not implement provider-specific tool formatting itself. CrewAI’s LLM documentation describes native SDK integrations for OpenAI, Anthropic, Google’s Gemini API, Azure, AWS Bedrock, and Snowflake Cortex, selected by the provider/model-id string you configure. All other providers run through LiteLLM. In either case, schema handling belongs to the client CrewAI routes to, not to CrewAI. For MCP, the crewai-tools package provides MCPServerAdapter and transport classes for stdio, SSE, and

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code. Taken together — faster on both passes for the jagged Ads shapes, competitive on dense, and far cheaper to build and maintain — TLX JFA is a better fit than the SOTA open-source FA4 for our Ads models. References [5] Kunlun: Establishing Scaling Laws for Massive-Scale Recommendation Systems through Unified Architecture Design — https://arxiv.org/abs/2602.10016 [6] FlashAttention-4: Algorithm and Kernel Pipelining Co-Design for Asymmetric Hardware Scaling — https://arxiv.org/abs/2603.05451

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found that InstructMesh could easily make their desired items. But what would someone who’s never 3D modeled anything think of their program? And could they really detect design flaws before fabrication? The team has TRELLIS recreate popular 3D models found on Thingiverse, a platform home to millions of 3D printable models, to help them find out. Nearly 80 percent of the models it generated were structurally flawed in some way. CSAIL researchers then asked novices to identify and fix these issue

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g it from both sides from the government. Zoë Schiffer : Yeah. And we have Lina Khan writing an op-ed in The New York Times today saying they actually can be tried under existing laws. We don't necessarily need to make new laws, with the big caveat that Congress would have to act. Zoë Schiffer : I personally think Republicans are going to do great in the midterms, but you can cut that because I am not reporting on politics and that's just my vibe check. Leah Feiger : I'm changing my mind constan

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Quick, a sales leader can build this from a dataset they already have access to and share it with other sales leaders without waiting for IT. The Amazon Quick app and data live in AWS infrastructure designed to be secure, with the customer’s row-level and column-level security. How it works Live Data in Apps centers on two workflows: building the app and viewing it. Let’s start with the build experience. Build the app With the dataset ready, describe the app in plain language and let the agent b

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A federal judge has dismissed a pair of antitrust lawsuits filed by Chegg and Rolling Stone parent company Penske Media Corporation, which accused Google of driving away web traffic with its AI-powered search features, as reported earlier by Reuters . US District Judge Amit Mehta takes Google’s side in a ruling on Wednesday , writing that PMC and Chegg’s claims don’t stand up to antitrust law. In lawsuits filed last year, Chegg and PMC accused Google of abusing its monopoly power by coercing pub

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existing experience. The problem turned out to be the content, not the model. We cover the intuition behind bandits, our extension to optimize an entire conversion funnel, and the AWS architecture behind the solution. We also share a code repository that you can use to test this approach on synthetic data and understand the method hands-on using Amazon SageMaker AI. Growing role of multi-armed bandits in the generative AI era A multi-armed bandit (MAB) is a reinforcement learning method built fo

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n (sometimes 1,000 digits): if few enough options remain, those numbers pin down the remaining coefficients exactly. The semi-numerical bootstrap seemed ideal for agentic AI. It draws on mathematics, physics, and computer science that no one person has mastered; it needs a great deal of coding and algorithm development; and it is checkable, since the same numerics let anyone, expert or not, verify the final answer against the integral to as many digits as they like by running two scripts. The co

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