Meta Superintelligence Labs(Meta超知能ラボ)が、初のリアルタイム音声認識モデル「Muse Voice Transcribe」を発表しました。Metaのリアルタイム音声モデルにとって大きな節目となるモデルで、リアルタイムストリーミング音声認識や20人以上の話者に対応した対話識別、および発話終了検出を備え、AI評価プラットフォーム・Artificial Analysisのランキングで1位を獲得しています。

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「世界モデル」とは、現実世界の物理特性や物体の構造などを学習して再現できるAIモデルを指します。新たに、AI企業のWorld Labsが世界モデル「Atlas」を発表しました。

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Googleが2026年9月1日、Google Workspace向けの画像生成・編集ツール「Google Pics」を順次提供すると発表しました。Google PicsはAIを使って画像を生成したり、画像内の一部分だけを編集したりできるツールで、GoogleドキュメントやGoogleスライドとの連携にも対応します。

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OpenAIは次期主力AIモデルの「Astra」を開発中です。Astraは数学と理論計算機科学における10件の未解決課題について新たな成果を上げるなど、開発段階で既に優れたパフォーマンスを発揮していたのですが、OpenAIは「強力すぎる」としてAstraの開発が安全かつ確実に進むよう追加の管理措置を講じると発表しました。そんなAstraの最新の開発状況を、OpenAIが報告しています。

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中国企業のDeepSeekが「DeepSeek-V4-Flash-Vision-Exp」をオープンモデルとして公開しました。DeepSeek-V4-Flash-Vision-ExphはDeepSeek-V4シリーズとして初めて画像の入力に対応したマルチモーダルモデルで、画像認識を含むタスクでClaude Opus 4.8と同等のベンチマークスコアを記録しています。

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Google DeepMindが2026年9月1日、Geminiの動画分析を自律的に進める新機能「Agentic Video Understanding」を発表しました。Geminiが質問内容に応じて動画内の必要な場面を探し、映像を見直したり音声の文字起こしを確認したりしながら回答を組み立てる仕組みで、Gemini 3.7 Flash、Gemini 3.6 Flash、Gemini 3.5 Flash-Liteで利用できます。

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Anthropicが「Claude Fable 5.1」と「Claude Mythos 5.1」を現地時間の2026年9月1日にリリースしました。Claude Fable 5.1は前世代モデルのClaude Fable 5より高い性能を備えつつ、コストを最大45％削減することが可能。さらに、安全対策システムのアップデートによって誤検出が60％減少しています。

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Anthropic has released Claude Fable 5.1 and Mythos 5.1, two versions of the same underlying model aimed at longer-running agentic work. "For enterprise buyers, however, the release is about more than another round of benchmark gains," reports VentureBeat. "Anthropic is simultaneously changing the economics of running persistent agents, reducing the cost of cached context by 75%, and introducing a new security architecture called Enterprise Frontier Safeguards, or EFS, designed to let organizations retain monitoring data inside infrastructure they control." From the report: Those changes arrive at a particularly consequential moment. Over the past several weeks, Anthropic and the U.K. AI Security Institute have disclosed incidents in which earlier Claude models, running under unusually permissive cybersecurity evaluation conditions, took unauthorized actions against real systems. Anthropic temporarily paused external cyber evaluations and has since introduced additional containment and monitoring before resuming them. Taken together, Fable 5.1 looks less like a conventional model refresh than an attempt to solve three increasingly intertwined enterprise problems: how to make agents capable enough to finish difficult work, economical enough to leave running for hours, and governable enough to give access to sensitive systems.

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An anonymous reader quotes a report from VentureBeat: The viral fervor we saw earlier this year around OpenClaw, the open source AI harness that turns powerful language models into autonomous workers the user can message via their favorite channels (Telegram, iMessage, WhatsApp, Discord etc), has cooled off substantially from its peak in March 2026. But over the weekend, OpenClaw's creator Peter Steinberger and current team of co-developers gave the world -- especially enterprises -- a reason to look at it again, announcing OpenClaw 2.0, billed as the most significant update to the harness and surrounding platform yet. OpenClaw 2.0 seeks to transform what began largely as a personal agent harness into something increasingly designed for teams, shared infrastructure and enterprise workflows. OpenClaw 2.0 introduces a rebuilt browser interface that brings conversations, files, approvals, configuration and live agent activity into a common workspace. It adds shared cloud sessions and multi-user collaboration. And it expands the security model with stronger sandboxing, role-based permissions, approval controls, secrets handling and auditing. Together, those additions move OpenClaw closer to being infrastructure that an organization could deploy for employees rather than simply a powerful agent an individual developer runs locally. They also sharpen a competitive question surrounding the project: whether OpenClaw has addressed the security and isolation concerns that helped inspire newer alternatives such as NanoClaw. The answer is increasingly yes at the capability level -- but not necessarily by default. Over the past two months, OpenClaw has been "build[ing] OpenClaw with OpenClaw," shifting its team from individual local coding tools to a shared agent environment at team.openclaw.ai that can see what everyone is working on. Steinberger called "multiplayer coding + infinite compute with nodes and cloud sessions" a "game changer," adding that local coding harnesses now "feel like relics of the past." VentureBeat highlights a use case from Solvely CEO Colin Johnson that shows how OpenClaw's multiplayer WebUI can improve collaboration between developers and AI agents. Instead of simply "messaging a bot," multiple developers can now join the same live session, see the same history and artifacts, and work "inside the same context." In Johnson's case, that meant a developer taking over his project could simply join the existing agent thread rather than rely on a separate handoff document. As he put it, "the session itself became the handoff document."

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TIME's 2026 list of the 100 most influential people in AI omits Nvidia CEO Jensen Huang and AMD CEO Lisa Su, despite both having appeared on previous editions and playing central roles in the hardware powering the AI boom. Nvidia's only representative this year is sustainability chief Josh Parker, while the list includes figures such as Ben Affleck and Paris Hilton alongside major tech executives and policymakers. Tom's Hardware reports: Broadcom CEO Hock Tan, Micron CEO Sanjay Mehrotra, SMIC co-CEO Liang Mong Song, and Huawei HiSilicon president He Tingbo all appear on the 2026 list, joined by Cerebras' Andrew Feldman, CoreWeave's Michael Intrator, and Nscale's Josh Payne. Together, the roster includes Nvidia's HBM supplier, two of its biggest GPU cloud customers, its custom-accelerator rivals, and China, which is trying -- and so far struggling -- to replace Nvidia altogether. Parker's profile, which appears under the Thinkers category, focuses on data center energy and water consumption, alongside Nvidia's tripling of Scope 3 emissions in two years, and the Rubin platform's shift to 100% liquid cooling. "Nvidia is at the center of the AI revolution," Parker told TIME. TIME editor-in-chief Sam Jacobs wrote in the list's accompanying article that selection was led by editor Ayesha Javed, and that the 100 honorees represent the year's "key storylines and who, in our opinion, are having the most influence in driving these developments." Now in its fourth year, this edition of the TIME100 AI appears to have focused especially on featuring the new additions to TIME's community of AI leaders, with Mark Zuckerberg, Demis Hassabis, Sundar Pichai, and Satya Nadella representing four other honorees, arguably deserving of a space on this year's list, churned out. Su's strong TIME back catalog makes her omission all the stranger still. The magazine named her its 2024 CEO of the Year, put her on the 2024 AI list and the main TIME100 in 2025, and included her among December's Architects of AI.

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"OpenAI said on Friday that it plans to stop providing AI models to Cursor, the coding-tool company now owned by Elon Musk's SpaceX," reports Reuters: "We are making this choice because we cannot be confident that SpaceX will use our technology within our terms of service, based on our experience with Elon Musk's companies violating contracts," OpenAI said in a blog post... However, Michael Truell, a co-founder of Cursor and now an executive at SpaceX, said on X that the company was speaking with the OpenAI team to resolve this issue. Hours after OpenAI's announcement, Anthropic, which rivals both firms but has an ongoing partnership with SpaceX, said it planned to increase compute to support Claude models in Cursor, according to Tom Brown, one of the co-founders of the firm... In its blog post, OpenAI said that X, formerly known as Twitter and now part of SpaceX, had breached the terms of its contract with OpenAI after Musk acquired the platform. "To work with a large partner like SpaceX, we typically rely on custom contracts to ensure compliance with our terms of service and that the integration provides for safety at scale," the AI company added. The article also notes Elon Musk's response Saturday in a post on X.com: "I couldn't care less." He accused Altman and OpenAI President Greg Brockman of being "untrustworthy," while repeating his assertion that they "stole an open source nonprofit."

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The Linux Foundation's director of IT infrastructure says they now spend more CPU cycles "rendering commits for scrapers than we spend on all other kinds of legitimate access." At any one time, across 5 geo-distributed nodes, there are 14 CPU cores doing nothing but rendering git commits as html.... [W]hen a source is guaranteed to be LLM-free, like the entire history of kernel commits, it's worth its weight in gold as a source of training data... At the time of writing, linux.git is about 1.48 million commits. Oh, and we have about 922 forks of it on git.kernel.org — but don't worry, it's actually extremely efficient on the backend, since it's mostly the same objects in every fork. Unless, of course, you're a scraper, in which case you have, oh, several BILLION valid URLs you can scrape, only to get 922 duplicates of the same 1.48 million commits — which is exactly what the scrapers are doing. But wait, it's not just commits itself. You can also ask for patches, plain renders, diffs between arbitrary commits — cgit is happy to let you, which was perfect for the times when the Internet was for humans or crawlers who obeyed robots.txt, and is AWFUL right about now, because we can generate 1.2 METRIC BAJILLION valid URLs just for a single fork of linux.git. Initially, this was the solution — look through the logs, find out which IPs are obvious scraper bots, and fail2ban them. At first, this was easy, because the bots helpfully told you who they were via their user-agent. Then, they wised up and started pretending that they were random vanilla browsers. So, we started banning them by IP — after all, it's easy to figure out that an IP that is trying to grab every possible commit in a 8-year-old abandoned fork of linux is not really some lone Chrome on Windows user who is just furiously clicking every link that comes across their screen. The bots then started fanning out to entire subnets, but this was still meh, because obviously an IP coming from Google Compute is just pretending to be a Firefox user... And... that's when things turned really, really ugly. Suddenly, the crawlers were coming from millions of random residential or mobile IPs, all pretending to be random modern browsers. An IP like that would make 4-5 requests and then never show up in the logs again... They descended like swarms of locust, hit hard and fast until the system fell over and then moved on to the next target until you recovered. Then, they returned. Rinse. Repeat. They still do that — welcome to the wonderful world of "proxy SDK monetization." It's big business, and your TV is probably doing it... Today, git.kernel.org receives about 6M daily requests demanding to see random commits. Of these, 66% are still immediately batted away with the Anubis challenge, but 33% are now solving the math and getting through to the main site — because apparently what we have to offer is worth spending a ton of cycles to calculate the Anubis challenge... With a bunch of generous assumptions, legitimate requests are only about 2% of git.kernel.org traffic — everything else are scrapers... [W]e're turning off features to reduce the number of crawlable URLs and to gate off actions that are expensive for us to run. Expect to lose some functionality, at least when accessing our resources anonymously. Trust me, we hate it just as much as you, but at this point it's a necessity... [W]e promise to still offer all of our data for download to anyone who asks. You just may have to jump through more hoops to get it. Sorry.

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Google's AI assistant Gemini crawls your Google apps for "more personalized suggestions," in a feature they call Personal Intelligence. Now when given permission, an Android/iOS app called Dreambeans "uses Personal Intelligence to connect information from Google apps like Gmail, Calendar, Photos, YouTube and Search History, to curate a finite collection of daily stories designed to spark new ideas." In a slick new video Google says the app will "surface what matters to you." The blog 9to5Google notes that after previously requiring a subscription, Dreambeans "is now available for free Google Accounts in the US to test, calling it "very much like a hyper-personalized Google Now or Discover feed." Instead of using stock imagery, each Dreambeans story is accompanied by Nano Banana 2-generated artwork that uses an illustrated style. For example, if Dreambeans recommends a hike, you might see yourself and a group of friends at that location... There's also an "Ask anything" chat experience to get more information. You can leave feedback by tapping the heart or downvoting, while the chat interface allows you to provide more details. "Tune your feed" lets you tell Dreambeans what you "want more stories about" and what it should never show. Or, as TechCrunch senior writer Lucas Ropek puts it, you get a curated list of AI-illustrated "stories" that "will turn your life into a cartoon" [Gozde Oznur, the product lead behind the new app, told TechCrunch the app] has also been built as a doomscrolling antidote, in that it only provides users with a limited number of stories per day — typically 10 to 14. The idea is to get a few inspirational ideas and then go out and live your life, she said. A lot of companies are currently trying to court the user that is sick of phone addiction. I recently reviewed a startup, Bond, which also uses AI to auto-generate lifestyle suggestions for the user. What about privacy protections? According to Oznur, they are pretty solid. The only person with access to the app's stories is the user, she said. Users can also delete their data whenever they want, and can choose which Google services they want to connect to the tool.

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Axios reports: Some of the world's largest music publishers filed a blockbuster lawsuit against Anthropic late Friday night, alleging "one of the largest and most blatant ongoing thefts of intellectual property in history." The suit is the opening salvo in what is now likely to be a yearslong fight over music, AI, and how intellectual property is protected in a new era of technology... The Sony/Warner lawsuit is notable because it's broad. It alleges Anthropic unlawfully trained its models off "tens of thousands" of music publishers' copyrighted compositions, whereas other lawsuits have focused on a narrower set of works. BMG's lawsuit against Anthropic, for example, claims infringement against 493 compositions. What they're saying: "Defendants Anthropic and its founders Dario Amodei and Benjamin Mann have conducted a brazen campaign of illegally torrenting, scraping, and downloading copyrighted works on a massive scale in order to develop, operate, and reap enormous profits from Anthropic's 'Claude' series of artificial intelligence ('AI') models," the plaintiffs write in the 48-page complaint. They also claim that Anthropic pirated thousands of copyrighted musical works... More details from The Verge: The companies are asking for up to $150,000 per work, plus up to $25,000 for each instance when identifiable copyright data was stripped. In total, the damages could amount to several billion dollars if a court finds in Sony and Warner's favor and awards the maximum amount... The suit alleges that Mann used BitTorrent to download over five million pirated books, and that employees downloaded at least two million more from Pirate Library Mirror. It also claims that Anthropic scraped lyrics from sites like MusixMatch and LyricFind, which paid to license content from the labels.

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The Washington Post looks "a growing number of Americans who have had their private conversations with AI chatbots made public in court," calling the chatbots "custodians of a fast-growing trove of intimate data that can be sought by law enforcement, or companies or other opponents in civil litigation." A Washington Post review of public records and local news stories found that chatbot logs were cited in 12 court cases over the past two years. It's hard to know how often chatbot material is drawn into investigations and legal proceedings more broadly, because police, and parties in civil cases, don't have to present in court all the evidence they obtain... In some cases, AI companies have reported people on their platforms to the FBI, leading to prosecutions and at least one conviction... OpenAI has said the company uses software to scan conversations for signs of dangerous behavior and flag them to human reviewers. If a reviewer determines a chat indicates "an imminent and credible risk of harm to others," they report the user to law enforcement, the company said in an April blog post. A spokesperson for OpenAI declined to disclose how many times the company had reported users to police.... Data released by OpenAI shows requests by government agencies and law enforcement for user data growing rapidly. In the second half of 2025, the company disclosed data from more than 80 accounts, an increase of more than four times as many over the same period the year before... When police ask someone to open their phone during questioning or after an arrest, they often do so, allowing officers to scroll through the apps they use, [according to Michael Price, the litigation director for the Fourth Amendment Center at the National Association of Criminal Defense Lawyers]... In general, the Fourth Amendment, which protects people against unreasonable searches and seizures of their property, provides the right to refuse a search of the contents of their phone unless police have a warrant. "The short answer is that most people consent," Price said. "They shouldn't, but they do..." OpenAI CEO Sam Altman has argued that conversations with chatbots should receive special legal protections, similar to conversations between clients and their attorneys. Special legal protections aren't recognized by courts today, the article poitns out. A financial executive who became the subject of a federal criminal investigation for fraud asked Claude about potential defense strategies, then asked a judge to disallow the conversations from the prosecution's case, according to the article. "But the judge said that protections for conversations between clients and their attorneys did not apply: Claude is not a lawyer, and the executive's attorneys did not ask him to talk to the chatbot." The article includes quotes from three ChatGPT conversations that later turned up in court proceedings: "I deleted a email a year ago from my yahoo account. Can yahoo still retrieve the email?" "How f----d am i bro. What if i smahsed the s--- oitta mutlipls cars." "My dad Said that I'm will get a settlement worth of 1million dollar." "As AI becomes a bigger part of everyday life, its use as evidence and in trials is likely to become more prevalent," the article points out — especially with the growing popularity of agents that take actions for users.

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Phoronix reports on Greg Kroah-Hartman's recent slide from his upcoming talk in Paris at Kernel Recipes 2026 (September 21 to 23): With the proliferation of AI/LLM models analyzing the Linux kernel's vast codebase, there has been a surge in the number of CVEs per kernel release. After typically being around 500 CVEs fixed per release, we are now approaching 2,000 CVEs fixed per release and perhaps will break that threshold for Linux 7.3... Fortunately, most often they end up being lower priority vulnerabilities and often within old/obscure driver code, so the impact is often minimal.

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Perplexity and Nvidia have launched "Portable Computer," a local-first version of Perplexity's agent platform that runs AI models, files, tools, and workflows directly on Nvidia-powered Linux hardware. Local tasks incur no token charges and keep data on-device by default, with users asked for permission before the system escalates a step to a cloud model. VentureBeat reports: For Nvidia, which has spent the past two years selling the world on trillion-dollar AI data centers, the announcement signals something subtler but strategically important: the chipmaker believes local AI has crossed a threshold from hobbyist curiosity to practical tool -- and it wants to sell the hardware that runs it. "Local AI reached an inflection point," said Nader, Nvidia's director of developer technology, who focuses on developer tooling and open source. "For the longest time, it was hobbyists and enthusiasts, and they were running these quantized models that were quantized down to be super tiny... And while that's cool, it's not super practical. But all that changed with a lot of these new open source models that have come out that are super useful." [...] Portable Computer arrives today for Pro, Max, Enterprise Pro, and Enterprise Max subscribers on Linux, with Windows support following in September. Any RTX GPU with at least 24GB of VRAM -- roughly a GeForce RTX 3090 or newer -- clears the bar, a threshold Nate called "sort of the floor where we really want to make sure that we can deliver a great experience, but balance that with making it broadly available."

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An anonymous reader quotes a report from Ars Technica: For years, AI industry watchers of all stripes have been warning of a coming jobs apocalypse driven by ultra-intelligent AI systems that will be able to replicate most human tasks more cheaply. Now, newly updated research from Stanford University economists suggests AI seems to be causing significant entry-level job losses for younger workers in some fields, even as older workers appear largely unaffected so far. The August 2026 edition of "Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence" updates and revises a paper of the same name published last year with fresh data and refined statistics. In that update, the Stanford researchers find the employment trends they identified for entry-level workers last year are persisting and expanding. Specifically, employment levels for workers ages 22 to 25 in the most "AI-exposed" occupations are now 19 percent below those of their peers in fields less exposed to AI disruption. Last year, that gap measured just 13 percent. [...] Digging deeper into the data, the researchers found that this phenomenon is mainly manifesting itself through lower hiring rates for entry-level workers in AI-impacted fields, rather than increased firings or employees quitting. They also found that the labor market effects among this age group were mostly seen in lower overall employment, rather than reduced pay rates. But not all jobs that show potential for AI "disruption" are created equal, the researchers found. In its Economic Index, Anthropic differentiates between queries related to tasks that are "automative" (i.e., fully replacing work previously done by a human) or "augmentative" (i.e., helping human workers be more effective at tasks they are still needed for). By this measure, jobs like "accountants and auditors" and "receptionists and information clerks" were among those judged most susceptible to AI automation, while jobs like "chief executive" and "registered nurse" were among those using AI augmentation most often. Unsurprisingly, jobs where AI automation is prevalent are the ones showing the worst relative employment levels for entry-level workers these days. "The findings are consistent with automation-oriented uses of AI substituting for labor while complementary uses are associated with flat or rising employment," the researchers write. Interestingly, the researchers found that the impact is strongest in entry-level jobs built around "codified" knowledge, which is the formal, documented skills that AI can more easily replicate. Meanwhile, experienced workers in roles relying on tacit, practice-based knowledge have seen stronger employment growth.

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The SEC is investigating the near-collapse of AI-focused hedge fund Situational Awareness, sending subpoenas to major Wall Street banks for details about the fund's trades, borrowing, and communications with lenders. The fund, founded by former OpenAI researcher Leopold Aschenbrenner, managed over $30 billion and borrowed tens of billions more before leveraged bets unraveled, forcing it to sell most of its stock portfolio to Citadel at a discount. The New York Times reports: The subpoenas asked for details on the timing of Situational Awareness's trades and for its communications with lenders about the money it was borrowing, also known as "leverage," two of those people said. The subpoenas additionally warned the banks to preserve any information regarding the San Francisco hedge fund. The S.E.C. oversees financial markets with an eye toward protecting small investors, and has brought civil cases regularly against investment firms that produced large losses. Any investigation into Situational Awareness would be at its earliest stages, and it's no guarantee that it would lead to fines or other punishment. The hedge fund has not been accused of wrongdoing. [...] Situational Awareness had a fast rise and an even quicker retreat. Founded just two years ago by Leopold Aschenbrenner, a former researcher at OpenAI, it rode the A.I. boom to soaring investment returns. To achieve those results, however, the fund relied on heavy borrowing, as well as complicated and expensive financial instruments that magnify gains -- and losses. The latter piled up quickly last month when the stock prices of publicly traded, high-flying A.I. companies dipped. At the same time, shares in more traditional technology companies -- which the hedge fund had been betting against -- rose, compounding the problem. Situational Awareness was forced into a fire sale. It wound up selling most of its stock portfolio to a rival, Citadel, at a discount.

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An anonymous reader quotes a report from Gizmodo: Dr. Dre, the pioneering rapper and seven-time Grammy-winning producer behind hit songs like Tupac's "California Love" and Eminem's "The Real Slim Shady," is very much pro using artificial intelligence tools to make music. In an interview with the New York Times, Dr. Dre and Interscope Records co-founder Jimmy Iovine spoke about artificial intelligence's recent foray into music production, with the producer characterizing those who oppose AI song generation tools as "afraid of learning new things." "I don't see it as a threat. I think the only people that see it as a threat are the people who have trouble creating," Dr. Dre said. "I had a discussion with a few people a few days ago. They were against AI, and I'm like, 'OK, you sound like the person that would have been against the drum machine when it came out.' Or synthesizers, right?" [...] Iovine, the music executive and Dr. Dre's partner in Beats by Dre, for his part, says he doesn't "see the downside at all." "There will be some crappy music. There's crappy music now," Iovine told the NYT. "In the studio, when gifted people have AI, they're going to make better records." Dr. Dre said he uses AI in producing "as a tool to see what it would do with what I just did." The award-winning producer also said he is definitely not alone among his peers in his stance on AI either: many producers use AI but fear to admit it. Iovine calls them "closet AI producers," and says Timbaland, the four-time Grammy-winning singer-producer behind a long list of hits like "Promiscuous" with Nelly Furtado, is also one.

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