搜索“RAG”

out for B-roll in our scene. The layout gets the scene arranged, and creates a placeholder where the B-roll will go. All you have to do is drop in the B-roll, which you can do by dragging-and-dropping it in, or recording it right into the scene. Or, grab some stock footage from Descript’s massive, searchable media library. You can adjust the layout however you want, and copy-paste it into other scenes if you plan to repeat that shot later in your video. And that’s all you need to do to create a

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x the litany of problems with the way it looks and sounds. Maybe your lighting is worse than you thought it’d be. Maybe cutting all your filler words left you with a relentless barrage of jump cuts. Maybe you stumbled over a single word in what’s otherwise a perfect take. Maybe your dog wandered into the frame, and not in a cute way. We’ve spent the past five years building toward a place where you can fix all of that, not by laboring over a timeline but by clicking features built to fix all of

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release to build on user feedback for future expansions. How does Underlord compare to previous versions? Underlord is a major leap from earlier Descript offerings because it leverages advanced AI to save editors time and stress. It offers more robust audio correction, faster transcription speeds, and smarter layer management for complex projects. According to the changelog, these upgrades address direct requests from the creator community. This iteration also smooths out the learning curve wit

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of low-hanging fruit is improving the general quality of RL environments. You don’t have to look far to see another new RL data company that’s crossed $100M or $1B in revenue. There are way more than I expected. The average outputs from this sector is remarkably low-quality. Countless researchers agree that lots of what they buy is frankly crap. At the same time, the leading labs see clear return on investment from buying the data. The way that many RL environments are cruddy is clearly fixable.

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ions you supply. It also returns per-option probabilities and a confidence field; score: rates input against ordered levels, indexed from 0. The score is a probability-weighted average of level indices OpenAI’s severity example makes the math concrete. Level probabilities of 0.1, 0.7 and 0.2 yield a score of 1.1. That value sits between ‘Workaround available’ and ‘Fully blocked’. When should you use Structured Outputs instead? OpenAI draws a clear line. Use Decisions for probabilities, choices o

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employee. “We’ve been making valid business cases for years to be paid a healthy salary, and instead they spent that money on software that most of us don’t really want.” (The average entry-level salary for New York City publishing employees at the Big Five and Scholastic was $47,583 in 2023.) In addition to Claude, staffers say HarperCollins has also purchased licenses for ChatGPT and Jasper, an agentic platform that promises “to run end-to-end marketing workflows.” At least one HarperCollins

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BpfJailer , an open-source eBPF security tool from Meta. It’s an experimental open-source rewrite of Meta’s internal closed-source eBPF security tool. Hiveminders into Cilium, Tetragon, or eBPF should know: Isovalent is also hosting its epic Hive Mind Mingle in Salt Lake… but sign up soon; attendance is limited. Before you go, explore how HPE Software helps IT teams do more with less complexity. If you haven’t bought your ticket yet, The New Stack readers get a special discount courtesy of the

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ssing git commit id after git commit -q or git -C commit; Fixed CLAUDE CODE TRANSCRIPT LOCAL GC dropping a message from the saved transcript when its text held a Unicode line or paragraph separator (U+2028, U+2029); Fixed claude purge leaving a prompt in the history file when its text held a Unicode line or paragraph separator (U+2028, U+2029); Windows: Fixed PowerShell commands longer than about 1 KB always asking for permission, so allow rules and read-only detection now apply up to 32 KB; Win

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Battery storage is now cheaper than a type of natural gas power plant favored by many data center developers, according to a new report from Wood Mackenzie. On every continent and in each of the 43 markets that Wood Mackenzie surveyed, four-hour duration batteries were less expensive than open-cycle gas turbines. The consultancy predicts that the cost of electricity from batteries will continue to decline while electrons from gas turbines will only grow more expensive in the coming decades. The

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managed infrastructure. In an email interview, Dahl explains that Celld had demonstrated how the Workers programming model could run on self-hosted infrastructure using object storage as its only dependency, offering a relatively straightforward deployment model. “Joining our efforts together means that we bring ideas from Celld directly into Workerd, and Workerd benefits from the Deno company’s runtime expertise,” he tells The New Stack . Dahl also confirmed that the combined project is expect

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Fade curves 〰️ Fades aren’t just linear anymore. Drag the node on the fade icon to shape exponential or logarithmic curves.

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Clip stretching ↔️ Shift-click-drag any clip to timestretch it. Match samples and found sounds to your project tempo in seconds.

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a few advantages over its competitors. For example, it picks up items with a pincer claw instead of a suction system. But the bigger difference is the business approach: Danu leverages AI to continuously improve the robot’s software. The approach is already seeing some traction. Danu has letters of interest from two large customers and $500,000 worth of signed contracts. More notably, more than 200 customers are in its sales pipeline, which gives the company a hook into the $20 billion market f

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Saw a video yesterday: A math PhD and her advisor spent 6 months proving a theorem. Before publishing, they asked ChatGPT. AI found a more elegant proof quickly, using an approach they'd never considered. They have an existential crisis now. But mathematicians shouldn't despair. We went through this in coding. Now we can't live without AI. Deep domain expertise + knowing how to leverage AI is a strong moat in this era.

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in Germany. All three startups were openly positioning their new models as the ones to pick if you’re concerned about AI sovereignty. Reflection’s new model enjoyed a blitz of coverage across Axios, Reuters, and Fortune, with the company press release explicitly saying it “advances the frontier for the Western open ecosystem.” Beam’s core claim is that it’s even more efficient on inference than Chinese model maker Z.ai’s highly touted GLM 5.2, though that isn’t Z.ai’s latest offering. Absent gov

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versation with Diogo, we found ourselves philosophically aligned with the mission behind this movement. Jev and TypeSafe as a company are much more aligned with developers ethos: pragmatic, composable, and deeply respectful of people who build. It’s a refreshing take in contrast to the rhetoric around the big labs about replacing software engineers and killing SaaS. TypeSafe believes AI is a tool that can make software more intelligent, and returns the power to the developers hands. The develope

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@BenHayum There have been national cyber emergencies before AI too. And there still would be if open models were banned. It’s about creating the right conditions for encouraging adaption and giving people the tools to defend themselves as well.

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luding how proactive Agent Mode should be, how it communicates uncertainty, and what baseline product knowledge it carries; A knowledge base uses a Retrieval Augmented Generation (RAG) approach. Postman has a large product surface that includes multiple request protocols, mock servers, monitors, documentation, the API Network, workspace governance, variables, helpers, code generation, request settings, and collection runs Encoding all of this in static prompts was not feasible, and most of it is

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on-call engineers spent a majority of their ticket response time negotiating the organized shutdown of non-preemptable workloads running on hosts with known maintenance problems. Tragedy of the commons When these problems emerged, we were slow to identify their root causes. Our initial attempts to ensure the most important work received GPU time were focused on tighter control of how priorities were set, and, ultimately, working around the priority-based scheduler by explicitly assigning GPU mon

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on-call engineers spent a majority of their ticket response time negotiating the organized shutdown of non-preemptable workloads running on hosts with known maintenance problems. Tragedy of the commons When these problems emerged, we were slow to identify their root causes. Our initial attempts to ensure the most important work received GPU time were focused on tighter control of how priorities were set, and, ultimately, working around the priority-based scheduler by explicitly assigning GPU mon

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