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A high-severity flaw impacting the LiteSpeed Cache plugin for WordPress is being actively exploited by threat actors to create rogue admin accounts on susceptible websites. The findings come from WPScan, which said that the vulnerability (CVE-2023-40000, CVSS score: 8.3) has been leveraged to set up bogus admin users with the names wpsupp‑user 

A high-severity flaw impacting the LiteSpeed Cache plugin for WordPress is being actively exploited by threat actors to create rogue admin accounts on susceptible websites. The findings come from WPScan, which said that the vulnerability (CVE-2023-40000, CVSS score: 8.3) has been leveraged to set up bogus admin users with the names wpsupp‑user Newsroomhttp://www.blogger.com/profile/[email protected]

Letos na jaře na trh přichází hned několik nových OLED panelů od dvou výrobců, mají mít běžné úhlopříčky i rozlišení a přijatelnou cenu. Monitory se lépe vypořádávají s problémy OLEDů a přibližují tuto technologii běžnému uživateli.

NASA se nebojí spolupracovat se SpaceX na velkých projektech především proto, že jí řídí Gwynne Shotwell a ne Elon Musk. V nedávném rozhovoru pro NPR to naznačil její ředitel Bill Nelson. Když víkendový moderátor All Things Accounted Scott Detrow připomněl, že Musk v posledních letech ve svých ...

Keynotes, physical security, playlists … the buck stops with Linda Gray Martin

Interview  The 33rd RSA Conference is underway this week, and no one feels that more acutely than the cybersecurity event's SVP Linda Gray Martin.…

'I'm blown away by the fact that they weren't using MFA'

Interview  The cybersecurity practices that led up to the stunning Change Healthcare ransomware infection indicate "egregious negligence" on the part of parent company UnitedHealth, according to Tom Kellermann, SVP of cyber strategy at Contrast Security.…

iboss Secure Web Gateway - Stored Cross-Site Scripting (XSS)

Clinic Queuing System 1.0 - RCE

Or at least it might well be if these trial programs work out, with some civil lib oversight etc etc etc

RSAC  AI is a double-edged sword in that the government can see ways in which the tech can protect and also be used to attack Americans, says US Homeland Security Secretary Alejandro Mayorkas.…

Dnes si naskenujeme QR kódy na zařízení s Linuxem, necháme počítač přečíst nahlas napsaný text, napíšeme a uspořádáme si poznámky a zahrajeme si hry na emulátoru konzole Nintendo 3DS. Nebude chybět ani blbinka.

Avoid traffic-redirecting snoops who have TunnelVision

A newly discovered vulnerability undermines countless VPN clients in that their traffic can be quietly routed away from their encrypted tunnels and intercepted by snoops on the network.…

In the first year alone, that's saved us all a lot of money and woe

Interview  As ransomware gangs step up their attacks against healthcare, schools, and other US critical infrastructure, CISA is ramping up a program to help these organizations fix flaws exploited by extortionists in the first place.…

Nothing like folks in Beijing lecturing us on the Constitution

TikTok and its China-based parent ByteDance sued the US government today to prevent the forced sale or shutdown of the video-sharing giant.…

As the adoption of generative artificial intelligence (genAI) continues to soar, the infrastructure to support that growth is currently running into a supply and demand bottleneck.

Sixty-six percent of enterprises worldwide said they would be investing in genAI over the next 18 months, according to IDC research. Among organizations indicating genAI will see increased IT spending in 2024, infrastructure will account for 46% of the total spend. The problem: a key piece of hardware needed to build out that AI infrastructure is in short supply.

The breakneck pace of AI adoption over the past two years has strained the industry’s ability to supply the special high-performance chips needed to run the process-intensive operations of genAI and AI in general. Most of the focus on processor shortages has been on the exploding demand for Nvidia GPUs and alternatives from various chip designers such as AMD, Intel, and the hyperscale datacenter operators, according to Benjamin Lee, a professor in the Department of Computer and Information Science at the University of Pennsylvania.

“There has been much less attention focused on exploding demand for high-bandwidth memory chips, which are fabricated in Korea-based foundries run by SK Hynix,” Lee said.

Last week, SK Hynix said its high-bandwidth memory (HBM) products, which are needed in combination with high-performance GPUs to handle AI processing requirements, are almost fully booked through 2025 because of high demand. The price of HBMs has also recently increased by 5% to 10%, driven by significant premiums and increased capacity needs for AI chips, according to market research firm TrendForce.

SK Hynix\’s HBM3 product with industry’s largest 24GB memory capacity features high-capacity and high-performance through stacking of 12 DRAM chips.

SK Hynix

HBM chips are expected to account for more than 20% of the total DRAM market value starting in 2024, potentially exceeding 30% by 2025, according to TrendForce Senior Research Vice President Avril Wu. “Not all major suppliers have passed customer qualifications for [high-performance HBM], leading buyers to accept higher prices to secure stable and quality supplies,” Wu said in a research report.

Why GPUs need high-bandwidth memory

Without HBM chips, a data center server’s memory system would be unable to keep up with a high-performance processor, such as a GPU, according to Lee. HBMs are what supply GPUs with the data they process. “Anyone who purchases a GPU for AI computation will also need high-bandwidth memory,” Lee said.

“In other words, high-performance GPUs would be poorly utilized and often sit idle waiting for data transfers. In summary, high demand for SK Hynix memory chips is caused by high demand for Nvidia GPU chips and, to a lesser extent, associated with demand for alternative AI chips such as those from AMD, Intel, and others,” he said.

“HBM is relatively new and picking up a strong momentum because of what HBM offers — more bandwidth and capacity,” said Gartner analyst Gaurav Gupta. “It is different than what Nvidia and Intel sell. Other than SK Hynix, the situation for HBM is similar for other memory players. For Nvidia, I believe there are constraints, but more associated with packaging capacity for their chips with foundries.”

While SK Hynix is reaching its supply limits, Samsung and Micron are ramping up HBM production and should be able to support the demand as the market becomes more distributed, according to Lee.

The current HBM shortages are primarily in the packaging from TSMC (i.e., chip-on-wafer-on-substrate or CoWoS), which is the exclusive supplier of the technology. According to Lee, TSMC is more than doubling its SOIC capacity and boosting capacity for CoWoS by more than 60%. “I expect the shortages to ease by the end of this year,” he said.

At the same time, more packaging and foundry suppliers are coming online and qualifying their technology to support NVIDIA, AMD, Broadcom, Amazon, and others using TSMC’s chip packaging technology, according to Lee.

Nvidia, whose production represents about 70% of the global supply of AI server chips, is expected to generate $40 billion in revenue from GPU sales this year, according to Bloomberg analysts. By comparison, competitors Intel and AMD are expected to generate $500 million and $3.5 billion, respectively. But all three are ramping production as quickly as possible.

Nvidia is tackling the GPU supply shortage by increasing its CoWoS and HBM production capacities, according to TrendForce. “This proactive approach is expected to cut the current average delivery time of 40 weeks in half by the second quarter [of 2024], as new capacities start to come online,” TrendForce report said in its report. “This expansion aims to alleviate the supply chain bottlenecks that have hindered AI server availability due to GPU shortages.”

Shane Rau, IDC’s research vice president for computing semiconductors, said that while demand for AI chip capacity is very high, markets are adapting. “In the case of server-class GPUs, they’re increasing supply of wafers, packaging, and memories. The increased supply is key because, due to their performance and programmability, server-class GPUs will remain the platform of choice for training and running large AI models.”

Chipmakers scramble to meet the demand for AI

Global spending on AI-focused chips is expected to hit $53 billion this year — and to more than double over the next four years, according to Gartner Research. So it’s no surprise that chipmakers are rolling out new processors as quickly as they can.

Intel has announced its plans for chips aimed at powering AI functions with its Gaudi 3 processors, and has said its Xeon 6 processors, which can run retrieval augmented generation (RAG) processes, will also be key. The Gaudi 3 GPU was purpose-built for training and running massive large language models (LLMs) that underpin genAI in data centers.

Meanwhile, AMD in its most recent earnings call, touted its MI300 GPU for AI data center workloads, which also has good market traction, according to IDC Group Vice President Mario Morales, adding that the research firm is tracking over 80 semiconductor vendors developing specialized chips for AI.

On the software side of the equation, LLM creators are also developing smaller models tailored for specific tasks; they require fewer processing resources and rely on local, proprietary data — unlike the massive, amorphous algorithms that boast hundreds of billions or even more than a trillion parameters.

Intel’s strategy going forward is similar: it wants to enable genAI on every type of computing device, from laptops to smart phones. Intel’s Xeon 6 processors will include some versions with onboard neural processing units (NPUs or “AI accelerators”) for use in workstations, PCs and edge devices. Intel also claims its Xeon 6 processors will be good enough to run smaller, more customized LLMs.

Even so, without HBMs, those processors would likely struggle to keep up with genAI’s high performance demands.

CPUs and Processors, Generative AI, Technology Industry

In March, we saw the launch of a “ChatGPT for music” called Suno, which uses generative AI to produce realistic songs on demand from short text prompts. A few weeks later, a similar competitor—Udio—arrived on the scene.

I’ve been working with various creative computational tools for the past 15 years, both as a researcher and a producer, and the recent pace of change has floored me. As I’ve argued elsewhere, the view that AI systems will never make “real” music like humans do should be understood more as a claim about social context than technical capability.

The argument “sure, it can make expressive, complex-structured, natural-sounding, virtuosic, original music which can stir human emotions, but AI can’t make proper music” can easily begin to sound like something from a Monty Python sketch.

After playing with Suno and Udio, I’ve been thinking about what it is exactly they change—and what they might mean not only for the way professionals and amateur artists create music, but the way all of us consume it.

Expressing Emotion Without Feeling It

Generating audio from text prompts in itself is nothing new. However, Suno and Udio have made an obvious development: from a simple text prompt, they generate song lyrics (using a ChatGPT-like text generator), feed them into a generative voice model, and integrate the “vocals” with generated music to produce a coherent song segment.

This integration is a small but remarkable feat. The systems are very good at making up coherent songs that sound expressively “sung” (there I go anthropomorphizing).

The effect can be uncanny. I know it’s AI, but the voice can still cut through with emotional impact. When the music performs a perfectly executed end-of-bar pirouette into a new section, my brain gets some of those little sparks of pattern-processing joy that I might get listening to a great band.

To me this highlights something sometimes missed about musical expression: AI doesn’t need to experience emotions and life events to successfully express them in music that resonates with people.

Music as an Everyday Language

Like other generative AI products, Suno and Udio were trained on vast amounts of existing work by real humans—and there is much debate about those humans’ intellectual property rights.

Nevertheless, these tools may mark the dawn of mainstream AI music culture. They offer new forms of musical engagement that people will just want to use, to explore, to play with, and actually listen to for their own enjoyment.

AI capable of “end-to-end” music creation is arguably not technology for makers of music, but for consumers of music. For now it remains unclear whether users of Udio and Suno are creators or consumers—or whether the distinction is even useful.

A long-observed phenomenon in creative technologies is that as something becomes easier and cheaper to produce, it is used for more casual expression. As a result, the medium goes from an exclusive high art form to more of an everyday language—think what smartphones have done to photography.

So imagine you could send your father a professionally produced song all about him for his birthday, with minimal cost and effort, in a style of his preference—a modern-day birthday card. Researchers have long considered this eventuality, and now we can do it. Happy birthday, Dad!

Mr Bown’s Blues. Generated by Oliver Bown using Udio [3.75 MB (download)] Can You Create Without Control?

Whatever these systems have achieved and may achieve in the near future, they face a glaring limitation: the lack of control.

Text prompts are often not much good as precise instructions, especially in music. So these tools are fit for blind search—a kind of wandering through the space of possibilities—but not for accurate control. (That’s not to diminish their value. Blind search can be a powerful creative force.)

Viewing these tools as a practicing music producer, things look very different. Although Udio’s about page says “anyone with a tune, some lyrics, or a funny idea can now express themselves in music,” I don’t feel I have enough control to express myself with these tools.

I can see them being useful to seed raw materials for manipulation, much like samples and field recordings. But when I’m seeking to express myself, I need control.

Using Suno, I had some fun finding the most gnarly dark techno grooves I could get out of it. The result was something I would absolutely use in a track.

Cheese Lovers’ Anthem. Generated by Oliver Bown using Suno [2.75 MB (download)]

 

But I found I could also just gladly listen. I felt no compulsion to add anything or manipulate the result to add my mark.

And many jurisdictions have declared that you won’t be awarded copyright for something just because you prompted it into existence with AI.

For a start, the output depends just as much on everything that went into the AI—including the creative work of millions of other artists. Arguably, you didn’t do the work of creation. You simply requested it.

New Musical Experiences in the No-Man’s Land Between Production and Consumption

So Udio’s declaration that anyone can express themselves in music is an interesting provocation. The people who use tools like Suno and Udio may be considered more consumers of music AI experiences than creators of music AI works, or as with many technological impacts, we may need to come up with new concepts for what they’re doing.

A shift to generative music may draw attention away from current forms of musical culture, just as the era of recorded music saw the diminishing (but not death) of orchestral music, which was once the only way to hear complex, timbrally rich and loud music. If engagement in these new types of music culture and exchange explodes, we may see reduced engagement in the traditional music consumption of artists, bands, radio and playlists.

While it is too early to tell what the impact will be, we should be attentive. The effort to defend existing creators’ intellectual property protections, a significant moral rights issue, is part of this equation.

But even if it succeeds I believe it won’t fundamentally address this potentially explosive shift in culture, and claims that such music might be inferior also have had little effect in halting cultural change historically, as with techno or even jazz, long ago. Government AI policies may need to look beyond these issues to understand how music works socially and to ensure that our musical cultures are vibrant, sustainable, enriching, and meaningful for both individuals and communities.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Image Credit: Pawel Czerwinski / Unsplash

Apple představil (keynote) iPad Pro s čipem Apple M4, předělaný iPad Air ve dvou velikostech a nový Apple Pencil Pro.

Apple iPad Pro má vysoký jas díky spojení dvou OLED panelů • Chlubí se extrémním výkonem díky novému čipu M4 • Levnější iPad Air poprvé přichází ve dvou velikostech

Dnešním dnem lze již také v Česku nakupovat na Google Store (telefony a sluchátka Google Pixel).

Spiral Linux is a Debian-based distribution that offers a range of desktop environments, making it stand out from other Linux distributions. In addition, it comes with a unique tool called SnapperGUI , which simplifies the process of creating operating system snapshots. These snapshots serve as a data recovery solution, allowing users to revert to a previously working state easily.