Signal’s Meredith Whittaker wants you to remember that AI chatbots ‘are not your friends’"These are not your friends. These are not conscious beings. These are not sentient interlocutors.”

Seeing the World in Radio Waves with the QuadRF
Although the basic principle of radio direction finding is easy to understand (measure the phase difference between different antennas, then calculate the angle of arrival from this difference), the radio hardware to actually implement this has historically been hard for hackers to access. The QuadRF project aims to change this by building a phase-coherent four-channel SDR which makes direction mapping easy (GitHub repository).
The QuadRF uses two boards: one to receive and pre-process radio waves, and a Raspberry Pi 5 for additional processing. The RF board has four patch antennas, each capable of either transmitting or receiving in the 4.9 GHz to 6.0 GHz range, with switchable right- or left-hand polarization. For on-device processing, it uses a Lattice ECP5 FPGA, which uses two MIPI cables to connect to the camera and display interfaces on the Raspberry Pi. These form a very high-speed data exchange, and after further processing, the Pi can pass data on over Ethernet or Wi-Fi. Individual QuadRF boards can connect together in a lattice grid to form larger phased arrays.
The QuadRF’s software shows off its real strength: it’s compatible with standard programs like GNU Radio, but it also hosts a few of its own programs. The most striking of these is an “RF camera” which scans its entire frequency range at 30 fps, tracking the direction of detected signals and visualizing them on a spatial plot. When overlaid on a camera feed, this plot lets one easily see the radio signals emitted from electronics; as an example, the creators tracked a drone in flight, even distinguishing the two radio transmitters on the drone.
This isn’t the first multi-antenna SDR we’ve seen, though this is the first that could transmit. It’s important to be careful, though: some applications of this kind of hardware run afoul of arms regulations.

Thanks to [Swake] for the tip!

Bitcoin rotations into altcoins collapses: Have altseasons 'disappeared'?BTC's crypto market dominance is holding above a key support, signaling Bitcoin may keep absorbing capital from altcoins and delay a broader altseason.

WAVDSP Primary VxPrimary Vx is a real-time, low-latency AI vocal cleanup product line from WAVDSP Neural Labs. It detects and separates the human voice from background noise and stage bleed, helping speech and singing stay clear in demanding environments. Keep the voice. Push the noise away. Primary Vx is designed for vocal microphones surrounded by real world sound: loud instruments, reflections, ambience, and unwanted bleed that normally follows the voice into the mix. Voice-aware cleanup in three stages. 1. Vx Source Detection. Identifies the vocal source in real time so the engine follows the performance, not the bleed around it. 2. Source Separation. Wipes unwanted background instruments, ambience, and bleed away from the vocal path. 3. Feedback Protection Helps you push more gain before feedback, with lower risk of ringing from the PA system. Designed with a multi-stage processing chain while keeping internal latency under 4.7 ms. This makes it practical for Front of House (FOH) workflows and other live vocal applications where response time matters. Read More

IK Multimedia introduce ReSing Doubling Available as a paid add-on for all versions, ReSing Doubling has been designed to help users create wider lead vocals, thicker backing parts and larger ensemble-style vocal arrangements without having to record multiple takes.

The Freddie Mercury Quote That Had Nothing to Do With MusicFreddie Mercury had everything the world could offer — and called himself the loneliest man alive. The quote that reveals who he really was when no one was performing for.

"In Times of Dragons" by Tori AmosUniversal/FontanaProducer: Tori Amos

Tori Amos’ 18th album sees the alt-pop veteran in full myth-maker mode, spinning political dread into fire-breathing allegory, where tyrants lurk like serpentine villains and hope flickers stubbornly underneath. It’s a sprawling 76-minute velvet coup that demands total surrender to its intricate, moss-covered melodies and, despite the record’s sheer density and occasional self-indulgence, it impressively navigates that tension between ancient folklore and modern chaos. In essence, it’s shadowy and just unhinged enough to remind us why she remains a high priestess of the avant-garde. Few artists could craft a campfire story for the end of the world that feels quite this essential. 

The post "In Times of Dragons" by Tori Amos first appeared on Music Connection Magazine.

Go eyes robotaxis and acquisitions after Japan’s biggest IPO of 2026. Here’s why it mattersGo’s IPO — Japan’s biggest so far this year — has done more than provide a much-needed boost to the country’s languishing listing season. It has also supplied the taxi-hailing app with the capital required to address an existential issue: Japan’s shortage of drivers. Go, which went public Tuesday, plans to use the ¥88.6 billion […]

Charles Schwab to enter prediction markets with S&P 500 wagers: WSJThe offering from the financial services company will reportedly only include yes-or-no bets on whether the S&P 500 closes above or below a target price.

FruityAlfred Software Track ManagementTrack Management is an offline audio workstation that turns your own track library into a production resource: database, analysis, stem separation, loop extraction, VST3 processing, BPM matching, mix discovery and export — in one continuous workflow. Import and analyze thousands of tracks locally (BPM, key, beats). The proprietary Loop Finder uses pure DSP — musical beat scoring, zero-crossing snap, bar quantization — to pull the best loops out of any track in your collection. Splice searches their library; Track Management searches yours. Split tracks into drums, bass, other and vocals with intelligent caching, then mix stems across tracks: drums from song A, vocals from song B — with per-stem 5-band EQ and VST3 inserts on every level (per-stem, master bus, single-track). Lock stems to a target BPM with high-quality time-stretching. Record your stem mix live, exactly as you hear it. The Mix Recommender finds compatible tracks by BPM, key, groove and energy. Offline-first: no subscription, no cloud. One-time purchase with lifetime updates. EN, DE, ES, FR, IT. Free unlimited trial. Works on any modern PC; NVIDIA GPU (CUDA) accelerates AI features. Read More

PCBs Straight from the MagazineIt’s never been easier to get a printed circuit board made. In fact, almost every electronics video out on the internet will incessantly remind you of this fact now. But making a custom PCB wasn’t always as straightforward as sending a KiCad file to a board house. Many DIY methods involve harsh chemicals and tedious processes, but did have the potential benefit of taking much less time than waiting on boards to arrive in the mail. [Bettina Neumryr] is demonstrating one of these older methods, called the toner transfer method, using a circuit that was printed directly in an old magazine.
The first part of the toner transfer method is to create an image that can be printed. Since this circuit came from a magazine, it is first scanned in to a computer and imported into GIMP, where it can be scaled to match the size of the components and then sharpened to make a crisp print. With the image ready, it’s time to print the image onto some toner transfer paper, ensuring that the printer in question is a laser printer which actually uses toner. From there, a sheet of blank copper PCB is prepared and then the toner is transferred by heating, in this case using a laminator. After that its etched, removing all of the copper not protected by the toner, and then the toner itself can be removed which leaves behind the copper traces.
For those of you who were around when toner transfer was in vogue, this video might not have much value. But for anyone who can’t use a board manufacturer for whatever reason or is looking for alternatives, a modern video showing the method could be much more useful and have better context for beginners than videos made a decade or more ago now. Some of those older methods include similar processes using inkjet printers instead, but there are more modern DIY methods as well using lasers or CNC machines too.

Two Notes Audio Engineering releases Genome Intro, a FREE amp and FX suite
In tandem with the release of Genome 2.0, Two Notes Audio Engineering has launched a free entry-level version, Genome Intro. Genome Intro is available in AU, VST3, and AAX formats for macOS and Windows. Even as a free offering, Genome Intro is a fairly comprehensive collection, including four amp models, fourteen pedals, five cabinets, and [...]
View post: Two Notes Audio Engineering releases Genome Intro, a FREE amp and FX suite

Akai Pro’s MPC One & MPC Key 37 get G2 upgrade The MPC One G2 and MPC Key 37 G2 both come loaded with a new eight-core processor, 4GB of RAM and 64GB of internal storage, and are powered by the company’s latest MPC operating system. 

“Until the major labels go through their lawsuits, there’s no way for artists or labels to fight back”: A massive music dataset is allegedly allowing AI to train on 12 million+ songs without permissionIf you’ve ever believed that your use of AI could go under the radar, think again. While The Atlantic’s AI Watchdog has been around for a while now, it’s currently gaining traction amongst musicians of all shapes and sizes – and the results seem to suggest that nobody is safe from their work being used against their will.
Last year, independent artists began filing lawsuits against Suno and Udio for “trampling” on the rights of smaller creatives. And, if the AI Watchdog’s findings are correct, the problem could be worse than it originally seemed.
Introduced in September 2025, the launch of the AI Watchdog tool found that more than “7.5 million books, 81 million research articles, 15 million YouTube videos, and writing from tens of thousands of movies and television shows” were allegedly all included in data sets used to train AI products.

READ MORE: Is AI seriously in mics now?

Prior to the release of the AI Watchdog tool, The Atlantic was hot on AI’s tail. Writer Alex Reisner in particular covered lots of oddities across the web, from noting AI’s “sneaky” addition to YouTube videos (the option to ‘improve clarity’ seemed to be a way of training AI), to calling out a The Common Crawl Foundation for allegedly “funnelling paywalled articles to AI developers”.
Earlier this week, Reisner discovered that “giant datasets of songs” have been shared within AI-development spaces. “One has 12 million tracks,” the writer claims. “Another has 9 million. The two smaller datasets each have more than 100,000. “The 12-million-track dataset, on its own, would take 91 years to listen to.”
Scarily, Reisner notes that the mass datasets have also already been downloaded “thousands of times”. Apparently, Google is among those who have downloaded one of the smaller datasets, reportedly downloading from the Free Music Archive to train AI models. Stability AI has also revealed it has trained on the Free Music Archive to train its systems.
In light of the new findings, many artists have been sharing their worries over their music being used against their will. Producer DJ Sabrina The Teen DJ in particular has clapped back at anyone calling their music “AI slop”, taking to X to say: “it’s funny how there were no accusations of my music sounding like AI slop until these datasets started getting used to generate slop.”

to everyone who thought my music sounded like ai slop, did you ever think it was because Suno was using a dataset that contained 22 of my songs?
it’s funny how there were no accusations of my music sounding like ai slop until these datasets started getting used to generate slop pic.twitter.com/SerSnaLO46
— DJSabrinaTheTeenDJ (@DJSTTDJ) June 18, 2026

Another X user also searched up Quedeca’s catalogue on AI Watchdog – and found that there were “295 grabs across 8 known data sets from various releases, snippets, videos, and corresponding lyrics from Genius”. In response, the artist could only respond with a bleak note of sarcasm: “Yayyyyy!”
Even smaller breakcore producer sophia_hjkl, who only has around has a combined following of around 10,000 across their X and Instagram accounts, is being looped into the shitstorm. “Suno and Udio [have] used138 of my songs across two of their datasets,” the artist writes. “This is almost my entire catalogue of music.”

the atlantic just published a searchable database of the music used by suno and udio. they used *one hundred and thirty eight* of my songs across two of their datasets. this is almost my entire catalogue of music. it's just about everything i've released from 2017 to 2024. pic.twitter.com/dnudQKY83J
— Sophiaaaahjkl;8901 (@sophia_hjkl) June 18, 2026

Currently, it seems no massive artists have spoken out about the AI Watchdog figures. But producer Vince Valholla, the head of Valholla Records, has posted a damning video on X. “Late last night I found out over 100+ songs from our catalogue were used to train AI models,” the owner says.
“To be honest, until the major labels go through their lawsuits, there’s no way for artists or labels to fight back,” he continues. “They literally scraped the best songs from our catalogue. I’m sick.”

Late last night I found out over 100+ songs from our catalog were used to train AI models. Thanks to The Atlantic, they leaked a database of millions of songs that have been used by the biggest AI music companies like Udio and Suno.
To be honest, until the major labels go… https://t.co/7D0kcVybwS pic.twitter.com/3d2cmei0u9
— Vince Valholla (@VinceValholla) June 19, 2026

Australia’s official music copyright team, APRA AMCOS, has also annoyed that it will be launching an investigation into The Atlantic’s findings. Opening on a list of notable acts – from Nick Cave to Kylie Minogue – a press release entitled “PROOF OF THEFT” condemns AI companies that have allegedly stolen mass datasets for training purposes.
With Australia officially rejecting copyright exception for AI platforms in October, APRA AMCOS isn’t too pleased with the findings. According to the press release, the company will be launching an investigation into the Australian and New Zealong songs that have been compromised. “No permission, no licence, no payment,” the company’s Chief Executive, Dean Ormston, writes. “These are not bargaining chips, they are the life’s work of Australian and New Zealand songwriters.”
Over on Reddit, many fans are frantically trying to find a way of helping their favourite artists from being used in AI training. “I doubt [someone] like [hypercore rapper] Jane Remover would want their shit used as birdfeed for an AI model,” one user writes.
Another user named Scott The Pisces, a small British producer, even notes that his own work is apparently included in some of the datasets. “Found 10 songs of mine on the dataset, and I’m not even famous,” he writes.
The post “Until the major labels go through their lawsuits, there’s no way for artists or labels to fight back”: A massive music dataset is allegedly allowing AI to train on 12 million+ songs without permission appeared first on MusicTech.

From Lionel Richie’s voice trademark bid to the Michael Jackson biopic box-office record… it’s MBW’s Weekly Round-upThe biggest headlines from the past few days...
Source