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Byl představen SCALE, tj. GPGPU toolchain umožňující spouštění CUDA programů na GPU od AMD. Za projektem stojí společnost Spectral Compute.

Vědci objevili podzemní tunel na Měsíci. Tento nález by mohl být klíčový pro budoucí lunární mise a snad i pro dlouhodobé pobyty astronautů. O objevu napsal časopis Nature Astronomy a představuje první přímý důkaz existence takového útvaru na Měsíci. Potvrzuje dlouholeté spekulace o rozsáhlých ...

Už na trhu jsou Oura, Ultrahuman a teď to zkouší i Samsung s Galaxy Ringem. Jsou podle vás chytré prsteny zajímavé zařízení pro sledování denní a noční aktivity? Láká vás ta nízká hmotnost a nenápadnost? Nebo raději dáte přednost chytrým hodinkám, které jsou sice větší, ale umí toho víc a nakonec ...

Texaská firma Aeromine Technologies nabízí zajímavou alternativu k fotovoltaickým panelům instalovaným na střechy domů. Patentovaná větrná turbína bez lopatek může fungovat jako lokální zdroj čisté energie, který najde využití zejména v městských zastavěných oblastech. Škálovatelná jednotka ...

Cybersecurity researchers said they discovered an accidentally leaked GitHub token that could have granted elevated access to the GitHub repositories of the Python language, Python Package Index (PyPI), and the Python Software Foundation (PSF) repositories. JFrog, which found the GitHub Personal Access Token, said the secret was leaked in a public Docker container hosted on Docker Hub. "This

Cybersecurity researchers said they discovered an accidentally leaked GitHub token that could have granted elevated access to the GitHub repositories of the Python language, Python Package Index (PyPI), and the Python Software Foundation (PSF) repositories. JFrog, which found the GitHub Personal Access Token, said the secret was leaked in a public Docker container hosted on Docker Hub. "This Newsroomhttp://www.blogger.com/profile/[email protected]

Apple Intelligence isn’t entirely Apple’s intelligence; just like so many other artificial intelligence (AI) tools, it also leans into all the human experience shared on the internet because all that data informs the AI models the company builds.

That said, the company explained where it gets the information it uses when it announced Apple Intelligence last month: “We train our foundation models on licensed data, including data selected to enhance specific features, as well as publicly available data collected by our web-crawler, AppleBot,” Apple explained.

Your internet, their product

Apple isn’t alone in doing this. In using the public internet this way, it is following the same approach as others in the business. The problem: that approach is already generating arguments between copyright holders and AI firms, as both sides grapple with questions around copyright, fair use, and the extent to which data shared online is commodified to pour even more cash into the pockets of Big Tech firms. 

Getty Images last year sued Stability AI for training its AI using 12 million images from its collection without permission. Individual creatives have also taken a stance against these practices. The concern is the extent to which AI firms are unfairly profiting from the work humans do, without consent, credit, or compensation.

In a small attempt to mitigate such accusations, Apple has told web publishers what they have to do to stop their content being used for Apple product development. 

Can you unmake an AI model?

What isn’t clear is the extent to which information already scraped by Applebot for use in Apple Intelligence (or any generative AI service) can then be winnowed out of the models Apple has already made. Once the model is created using your data, to what extent can your data be subsequently removed from it? The learning — and potential for copyright abuse — has already been baked in.

But where is the compensation for those who’ve made their knowledge available online? 

In most cases, the AI firms argue that what they are doing can be seen as fair use rather than being any violation of copyright laws. But, given that what constitutes fair use differs in different nations, it seems highly probable that the evolving AI industry is heading directly toward regulatory and legal challenges around their use of content.

That certainly seems to be part of the concern coming from regulators in some jurisdictions, and we know the legal framework around these matters is subject to change. This might also be part of what has prompted Apple to say it will not introduce the service in the EU just yet.

Move fast and take things

Right now, AI companies are racing faster than government regulation. Some in the space are attempting to side-step such debates by placing constraints around how data is trained. Adobe, for example, claims to train its imaging models only using legitimately licensed data. 

In this case, that means Adobe Stock images licensed content and older content that is outside of copyright.

Adobe isn’t just being altruistic in this — it knows customers using its generative AI (genAI) tools will be creating commercial content and recognizes the need to ensure its customers don’t end up being sued for illegitimate use of images and other creative works. 

What about privacy?

But when it comes to Apple Intelligence, it looks like the data you’ve published online has now become part of the company product, with one big exception: private data.

“We never use our users’ private personal data or user interactions when training our foundation models, and we apply filters to remove personally identifiable information like social security and credit card numbers that are publicly available on the Internet,” it said. 

Apple deserves credit for its consistent attempts to maintain data privacy and security, but perhaps it should develop a stronger and more public framework toward the protection of the creative endeavors of its customer base.

Please follow me on Mastodon, or join me in the AppleHolic’s bar & grill and Apple Discussions groups on MeWe.

'It seems like they really don't have a full grasp of what's going on with this patch'

Exclusive  A Microsoft zero-day vulnerability that Trend Micro's Zero Day Initiative team claims it found and reported to Redmond in May was disclosed and patched by the Windows giant in July's Patch Tuesday – but without any credit given to ZDI.…

Amazon.de je tím hlavním, přes který byste měli v ČR nakupovat • Má ale svá úskalí týkající se češtiny, cen a dopravy • Prozradíme trky, které se vám budou hodit

Během konference v Los Angeles došlo i na malou taktovací akci, kde se podařilo pokořit světový rekord v Cinebench R23 a nějaké další.

Company keeps quiet amid high-profile compromises

Security researchers are claiming a spate of DNS hijackings at web3 businesses is linked to Squarespace's acquisition of Google Domains last year.…

Exim is one of Unix-like systems' most widely used mail transfer agents. It's essential for email delivery and handling and is a significant part of the Internet email infrastructure.

The AI landscape is undergoing a transformative shift as chipmakers, traditionally focused on hardware innovation, are increasingly recognizing the pivotal role of software.

This strategic shift is redefining the AI race, where software expertise is becoming as crucial as hardware prowess.

AMD’s recent acquisitions: a case study

AMD’s recent acquisition of Silo AI, Europe’s largest private AI lab, exemplifies this trend. Silo AI brings to the table a wealth of experience in developing and deploying AI models, particularly large language models (LLMs), a key area of focus for AMD.

This acquisition not only enhances AMD’s AI software capabilities but also strengthens its presence in the European market, where Silo AI has a strong reputation for developing culturally relevant AI solutions.

“Silo AI plugs important capability gap [for AMD] from software tools (Silo OS) to services (MLOps) to helping tailor sovereign and open source LLMs and at the same time expanding its footprint in the important European market,” said Neil Shah, partner & co-founder at Counterpoint Research.

AMD’s move follows its previous acquisitions of Mipsology and Nod.ai, further solidifying its commitment to building a robust AI software ecosystem. Mipsology’s expertise in AI model optimization and compiler technology, coupled with Nod.ai’s contributions to open-source AI software development, provides AMD with a comprehensive suite of tools and expertise to accelerate its AI strategy.

“These strategic moves strengthen AMD’s ability to offer open-source solutions tailored for enterprises seeking flexibility and interoperability across platforms,” said Prabhu Ram, VP of industry research group at Cybermedia Research. “By integrating Silo AI’s capabilities, AMD aims to provide a comprehensive suite for developing, deploying, and managing AI systems, appealing broadly to diverse customer needs. This aligns with AMD’s evolving market position as a provider of accessible and open AI solutions, capitalizing on industry trends towards openness and interoperability.”

Beyond AMD: A broader industry trend

This strategic shift towards software is not limited to AMD. Other chip giants like Nvidia and Intel are also actively investing in software companies and developing their own software stacks.

“If you look at the success of Nvidia, it is driven not by silicon but by software (CUDA) and services (NGC with MLOps, TAO, etc.) it offers on top of its compute platform,” Shah said. “AMD realizes this and has been investing in building software (ROCm, Ryzen Aim, etc.) and services (Vitis) capabilities to offer an end-to-end solution for its customers to accelerate AI solution development and deployment.”

Nvidia’s recent acquisition of Run:ai and Shoreline.io, both specializing in AI workload management and infrastructure optimization, also underscores the importance of software in maximizing the performance and efficiency of AI systems.

But this doesn’t mean chipmakers follow similar trajectories toward their goals. Manish Rawat, semiconductor analyst at Techinsights pointed out that for a large part, Nvidia’s AI ecosystem has been established through proprietary technologies and a robust developer community, giving it a strong foothold in AI-driven industries.

“AMD’s approach with Silo AI signifies a focused effort to expand its capabilities in AI software, positioning itself competitively against Nvidia in the evolving AI landscape,” Rawat added.

Another relevant example in this regard is Intel’s acquisition of Granulate Cloud Solutions, a provider of real-time continuous optimization software. Granulate assists cloud and data center clients in optimizing compute workload performance while lowering infrastructure and cloud expenses.

Software to drive differentiation

The convergence of chip and software expertise is not just about catching up with competitors. It’s about driving innovation and differentiation in the AI space.

Software plays a crucial role in optimizing AI models for specific hardware architectures, improving performance, and reducing costs. Eventually, software could decide who rules the AI chip market.

“The bigger picture here is that AMD is obviously competing with NVIDIA for supremacy in the AI world,” said Hyoun Park, CEO and chief analyst at Amalgam Insights. “Ultimately, this is not just a question of who makes the better hardware, but who can actually back the deployment of enterprise-grade solutions that are high-performance, well-governed, and easy to support over time. And although Lisa Su and Jensen Huang are both among the absolute brightest executives in tech, only one of them can ultimately win this war as the market leader for AI hardware.” 

The rise of full-stack AI solutions

The integration of software expertise into chip companies’ offerings is leading to the emergence of full-stack AI solutions. These solutions encompass everything from hardware accelerators and software frameworks to development tools and services.

By offering a comprehensive suite of AI capabilities, chipmakers can cater to a wider range of customers and use cases, from cloud-based AI services to edge AI applications.

For instance, Silo AI, first and foremost, brings an experienced talent pool, especially working on optimizing AI models, tailored LLMs, and more, according to Shah. Silo AI’s SIloOS particularly is a very powerful addition to AMD’s offerings allowing its customer to leverage advanced tools and modular software components to customize AI solutions to their needs. This was a big gap for AMD.

“Thirdly, Silo AI also brings in MLOps capabilities which are a critical capability for a platform player to help its enterprise customers deploy, refine and operate AI models in a scalable way,” Shah added. “This will help AMD develop a service layer on top of the software and silicon infrastructure.”

Implications for enterprise tech

The shift of chipmakers from purely hardware to also providing software toolkits and services has significant ramifications for enterprise tech companies.

Shah stressed that these developments are crucial for enabling enterprise and AI developers to fine-tune their AI models for enhanced performance on specific chips, applicable to both training and inference phases.

This advancement not only speeds up product time-to-market but also aids partners, whether they are hyperscalers or manage on-premises infrastructures, in boosting operational efficiencies and reducing total cost of ownership (TCO) by improving energy usage and optimizing code.

“Also, it’s a great way for chipmakers to lock these developers within their platform and ecosystem as well as monetize the software toolkits and services on top of it. This also drives recurring revenue, which chipmakers can reinvest and boost the bottom line, and investors love that model,” Shah said.

The future of AI: a software-driven landscape

As the AI race continues to evolve, the focus on software is set to intensify. Chipmakers will continue to invest in software companies, develop their own software stacks, and collaborate with the broader AI community to create a vibrant and innovative AI ecosystem.

The future of AI is not just about faster chips — it’s about smarter software that can unlock the full potential of AI and transform the way we live and work.

Na nedávné konferenci AMD Tech Days, která se odehrála v Los Angeles společnost AMD představila zajímavou novinku. A to sice přetaktování RAM za běhu systému.

Oživeno 15. 7. | Electro World už na svém webu začal informovat nakupující, že se obchod změní na Datart. Přesný časový rámec neuvádí, protože potrvá několik měsíců, než se převlečou kamenné prodejny. E-shop už ale brzy čekají první změny. Přesně za měsíc, 15. srpna, skončí věrnostní program. ...

Kdyby tohle udělali přímo Microsoft a Apple před třiceti lety, mohl svět vypadat jinak.

A whistleblower letter obtained by The Washington Post accuses OpenAI of illegally restricting employees from communicating with authorities about the risks their technology may pose. The letter was reportedly sent to the US Securities and Exchange Commission (SEC) — the agency that oversees the trading of securities — urging the regulators to review OpenAI.

According to the letter, OpenAI allegedly used illegal non-disclosure agreements to, among other things, force employees to refrain from whistle-blowing incentives and it required them to state whether they had contact with authorities.

OpenAI has come under previous criticism for the restrictive design of its non-disclosure agreements, which it said it would modify. In a statement to The Washington Post, OpenAI spokesperson Hannah Wong said: “Our whistleblower policy protects employees’ rights to make protected disclosures.”

More OpenAI news:

• OpenAI is working on new reasoning AI technology
• OpenAI whistleblowers seek SEC probe into ‘restrictive’ NDAs with staffers
• OpenAI: Musk’s control issues at heart of ongoing rift
• OpenAI models still available in China via Azure cloud despite company ban